AI Creative & Design Jobs

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At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. We work in tight, skilled teams, prioritize clarity over complexity, and continuously evolve through curiosity, data, and craftsmanship.  We’re seeking technologists and problem solvers who thrive in fast-paced environments, love collaborating with great talent, and approach every day like it’s Day 1. We're a globally diverse team with hubs in New York City, Mountain View, Latin America, and India. If you're driven by continuous learning, rapid pivots, and the challenges of building in a high-growth startup, we’d love to talk. This is more than a job—it’s a journey. We're currently expanding our research team, and looking for an experienced Research Lead  specializing in Conversational AI & Speech. In this role, you will work on solving scientific challenges related to Conversational AI to build domain-specific, real-world solutions.  Your contributions will be through both applying your expertise as an IC, and through your leadership of a team of researchers.   You will have the opportunity to leverage the massive amounts of data generated by our products to ask fundamental research questions, while deploying AI features into real-world applications.What you'll doLead, mentor and grow a team of research scientists and engineers working on spoken conversational AI research initiatives.  Hands-on Research: Be deeply involved in hands-on technical work in any and all aspects of research projects from early exploration to working prototypes to achieve successful real-world applicationsResearch Leadership: Identify promising applications of AI relevant to ASAPP’s core mission, formulate and advocate for research programs in those areas, and take ownership of driving impactful research initiativesCollaboration & Advocacy: Work with cross-functional teams to socialize your research findings, advocate for their application, and guide the productization of those findings to improve customer experience solutionsDocumentation & Publication: Document significant experimental results, contribute to publishing peer-reviewed papers, and participate in patenting innovationsMentorship: Mentor and guide junior researchers, helping them develop their skills in independent research and the communication of their findings.What we're looking forEducation: PhD in a relevant field (such as Computer Science, Electrical Engineering, Linguistics, etc.), along with significant experience in research.Technical Expertise: Strong research experience in Speech systems and/or Speech LLMs, including practical knowledge of algorithm design, model development, and experimental evaluation.Mentorship & Leadership: Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.Hands-on Contribution: As an individual contributor, you’ll be expected to lead experiments, perform hands-on research, and drive the execution of innovative projectsEnthusiasm: A passion for continued learning and deepening expertise in machine learning and AI, with a strong desire to apply research in impactful ways.What we'd like to seeExperience building & growing an applied research team in academia or industry.Experience with Spoken Conversational AI applications or Speech LLMs.Experience developing and leading long term research programs.Experience collaborating across functions to productize research, and to improve production systems.A collaborative mindset, eager to share research findings and drive their application across product teams.Experience in a startup environment, with the ability to balance deep research and rapid execution. 270,000 - 290,000 a yearCompensation is a combination of salary and performance bonus Separately, you will also receive an equity grantASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at careers@asapp.com to obtain assistance. #LI-AG1 #LI-Hybrid

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At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. We work in tight, skilled teams, prioritize clarity over complexity, and continuously evolve through curiosity, data, and craftsmanship. We’re seeking technologists and problem solvers who thrive in fast-paced environments, love collaborating with great talent, and approach every day like it’s Day 1. We're a globally diverse team with hubs in New York City, Mountain View, Latin America, and India—embracing both hybrid and remote work to bring the best minds together, wherever they are. If you're driven by continuous learning, rapid pivots, and the challenges of building in a high-growth startup, we’d love to talk. This is more than a job—it’s a journey. Research Engineers at ASAPP work to fundamentally advance the science of AI towards our goal of deploying domain specific real-world AI solutions, and to apply those advances to our products.  They leverage the massive amounts of data generated by our products, and our ability to deploy AI features into real-world use to ask and address fundamental research questions critical to our product. We are expanding our research team, and are looking for candidates with masters degrees; research experience in Conversational AI, Speech systems, LLMs, or Machine Learning; outstanding communication skills; and strong software engineering skills. If you thrive in an environment of deep thinking, impactful research, and startup-paced execution, ASAPP is an ideal environment for you.What you’ll doDesign, develop and evaluate novel techniques in AI to advance the capabilities and impact of ASAPP’s products.Collaborate with product & engineering teams to ensure the success of projects during the research phase and after.Build and maintain research datasets, infrastructure and toolkitsCollaborate with other functions at ASAPP to identify research opportunities.What you’ll needA masters degree in any area of machine learning; or equivalent experienceRelevant academic or industrial research experienceThe scientific curiosity and tenacity required to solve hard research problems.Strong communications and interpersonal skillsAbility to work with a diverse team in a fast-paced environmentWe’d like to seePeer reviewed publications in any area of machine learningStrong software engineering experienceExperience in Speech systems research and engineering.Experience fine-tuning LLMs.Ability to maintain a fun, casual, professional and productive team atmosphereThe ability to communicate in a courteous, tactful, and concise mannerEnthusiasm and the ability to thrive in an atmosphere of constant changeBenefitsCompetitive compensationStock optionsICICI Lombard General Insurance LTDOnsite lunch & dinner stipendConnectivity (mobile phone & internet) stipendWellness perksMac equipmentLearning & development stipendParental leave, including 6 weeks paternity leaveASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at careers@asapp.com to obtain assistance. #LI-SL1 #LI-Hybrid

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At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. We work in tight, skilled teams, prioritize clarity over complexity, and continuously evolve through curiosity, data, and craftsmanship. We’re seeking technologists and problem solvers who thrive in fast-paced environments, love collaborating with great talent, and approach every day like it’s Day 1. We're a globally diverse team with hubs in New York City, Mountain View, Latin America, and India—embracing both hybrid and remote work to bring the best minds together, wherever they are. If you're driven by continuous learning, rapid pivots, and the challenges of building in a high-growth startup, we’d love to talk. This is more than a job—it’s a journey. Research Engineers at ASAPP work to fundamentally advance the science of AI towards our goal of deploying domain specific real-world AI solutions, and to apply those advances to our products.  They leverage the massive amounts of data generated by our products, and our ability to deploy AI features into real-world use to ask and address fundamental research questions critical to our product. We are expanding our research team, and are looking for candidates with masters degrees; research experience in Conversational AI, Speech systems, LLMs, or Machine Learning; outstanding communication skills; and strong software engineering skills. If you thrive in an environment of deep thinking, impactful research, and startup-paced execution, ASAPP is an ideal environment for you.What you’ll doDesign, develop and evaluate novel techniques in AI to advance the capabilities and impact of ASAPP’s products.Collaborate with product & engineering teams to ensure the success of projects during the research phase and after.Build and maintain research datasets, infrastructure and toolkitsCollaborate with other functions at ASAPP to identify research opportunities.What you’ll needA masters degree in any area of machine learning; or equivalent experienceRelevant academic or industrial research experienceThe scientific curiosity and tenacity required to solve hard research problems.Strong communications and interpersonal skillsAbility to work with a diverse team in a fast-paced environmentWe’d like to seePeer reviewed publications in any area of machine learningStrong software engineering experienceExperience in Speech systems research and engineering.Experience fine-tuning LLMs.Ability to maintain a fun, casual, professional and productive team atmosphereThe ability to communicate in a courteous, tactful, and concise mannerEnthusiasm and the ability to thrive in an atmosphere of constant changeBenefitsCompetitive compensationStock optionsHealthcare for the family groupUSD 150 per month in flexible benefitsMac equipment3 weeks of vacationEnglish lessonsASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at careers@asapp.com to obtain assistance. #LI-SL1 #LI-Remote

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About the Company:Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!We are looking for an SDE II – Agentic Engineer to build and scale agentic workflows and tools using Netomi’s no-code platform. This role requires strong software engineering fundamentals combined with prompt engineering and API-driven automation to power reliable, autonomous AI agents.Key ResponsibilitiesDesign and write high-quality prompts for LLM-based agents (GPT-class models preferred).Build agentic tools and workflows using Netomi’s no-code platform (similar to Workato, Zapier, n8n).Integrate external and internal APIs, including authentication, data mapping, and error handling.Implement unit tests, debug issues, and ensure reliability of agent workflows.Apply engineering best practices and design patterns such as retries, timeouts, idempotency, and lazy loading.Optimize agents for performance, cost, and fault tolerance.Collaborate with Product, QA, and Delivery teams to ship production-grade agentic solutions.Required Skills & Qualifications3–6 years of experience as a Software Development Engineer or similar role.Strong understanding of prompt engineering and LLM behavior.Hands-on experience with REST APIs, webhooks, and JSON-based integrations.Solid experience in unit testing, debugging, and troubleshooting.Knowledge of resilient system design patterns and non-happy path handling.Nice to HaveExperience with no-code/low-code automation platforms.Exposure to agentic AI, conversational AI, or workflow orchestration systems.Familiarity with observability and monitoring in production systems.Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

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About the Company:Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!About the RoleAs an Agentic Product Manager at Netomi, you will be the strategic and technical owner responsible for designing, architecting, and deploying large-scale Agentic AI solutions for enterprise customers. You will translate complex business processes into AI-driven workflows, define integration blueprints, and guide customers through their transformation to autonomous AI agents. You will work closely with Customers, CSM, Integration Engineers, QA, Product, and Engineering to ensure end-to-end success of every deployment.ResponsibilitiesLead discovery sessions with enterprise customers to understand business processes, operations, workflows, KPIs, and constraints.Identify automation opportunities and design agentic orchestration strategies using Netomi’s AI platform.Build detailed solution blueprints — workflows, data exchanges, escalation logic, guardrails, analytics, and agent lifecycle design.Define end-to-end Agentic AI architectures, covering intents, actions, tools, integration points, and decision logic.Work with customer technical teams to map integration dependencies (APIs, events, SSO, CRMs, ticketing systems, internal tools).Own the creation of integration design documents and support Integration Engineers during implementation.Ensure agent workflows comply with enterprise standards (security, reliability, audit, governance).Collaborate with Product & Engineering to translate customer requirements into features or enhancements.Serve as the product owner during deployment — driving priorities, clarifications, acceptance criteria, and workflow evolution.Validate solution behavior end-to-end with QA and guide test plans, scenario tests, and success criteria.Conduct user-experience reviews of agent outputs and behavior tuning.Act as a trusted advisor to customer stakeholders (CX, Ops, Digital Transformation, Engineering).Present architectural recommendations, best practices, and roadmap suggestions.Train customer teams on agentic workflows, governance, and performance improvement strategies.Ensure projects are delivered on time with high quality, low rework, and measurable impact.Drive continuous improvement through playbooks, reusable workflow templates, and integration patterns.Maintain deep expertise in agentic AI, LLMs, workflow orchestration, and enterprise systems.Requirements6-10 years in Solutions Architecture / Implementation Consulting / Product Consulting / Workflow Design for enterprise SaaS or AI platforms.Experience designing complex workflows and integrations across enterprise systems.Ability to gather requirements, translate them into technical specifications, and drive execution.Customer-facing consulting experience with strong communication & facilitation skills.Understanding of REST APIs, event-driven systems, data flows, and enterprise integrations.Experience working cross-functionally with CSM, engineering, product, and QA teams.Nice-to-HaveBackground in Conversational AI, Agentic AI, RPA, Automation, CRM/Ticketing, or LLM-based products.Hands-on experience defining business logic, decision trees, or automated workflows.Experience with enterprises such as airlines, BFSI, telecom, retail, or large-scale customer support environments.Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

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About the Company:Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!About the RoleAs an Agentic Product Manager at Netomi, you will be the strategic and technical owner responsible for designing, architecting, and deploying large-scale Agentic AI solutions for enterprise customers. You will translate complex business processes into AI-driven workflows, define integration blueprints, and guide customers through their transformation to autonomous AI agents. You will work closely with Customers, CSM, Integration Engineers, QA, Product, and Engineering to ensure end-to-end success of every deployment.ResponsibilitiesLead discovery sessions with enterprise customers to understand business processes, operations, workflows, KPIs, and constraints.Identify automation opportunities and design agentic orchestration strategies using Netomi’s AI platform.Build detailed solution blueprints — workflows, data exchanges, escalation logic, guardrails, analytics, and agent lifecycle design.Define end-to-end Agentic AI architectures, covering intents, actions, tools, integration points, and decision logic.Work with customer technical teams to map integration dependencies (APIs, events, SSO, CRMs, ticketing systems, internal tools).Own the creation of integration design documents and support Integration Engineers during implementation.Ensure agent workflows comply with enterprise standards (security, reliability, audit, governance).Collaborate with Product & Engineering to translate customer requirements into features or enhancements.Serve as the product owner during deployment — driving priorities, clarifications, acceptance criteria, and workflow evolution.Validate solution behavior end-to-end with QA and guide test plans, scenario tests, and success criteria.Conduct user-experience reviews of agent outputs and behavior tuning.Act as a trusted advisor to customer stakeholders (CX, Ops, Digital Transformation, Engineering).Present architectural recommendations, best practices, and roadmap suggestions.Train customer teams on agentic workflows, governance, and performance improvement strategies.Ensure projects are delivered on time with high quality, low rework, and measurable impact.Drive continuous improvement through playbooks, reusable workflow templates, and integration patterns.Maintain deep expertise in agentic AI, LLMs, workflow orchestration, and enterprise systems.Requirements4–10 years in Solutions Architecture / Implementation Consulting / Product Consulting / Workflow Design for enterprise SaaS or AI platforms.Experience designing complex workflows and integrations across enterprise systems.Ability to gather requirements, translate them into technical specifications, and drive execution.Customer-facing consulting experience with strong communication & facilitation skills.Understanding of REST APIs, event-driven systems, data flows, and enterprise integrations.Experience working cross-functionally with CSM, engineering, product, and QA teams.Nice-to-HaveBackground in Conversational AI, Agentic AI, RPA, Automation, CRM/Ticketing, or LLM-based products.Hands-on experience defining business logic, decision trees, or automated workflows.Experience with enterprises such as airlines, BFSI, telecom, retail, or large-scale customer support environments.Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

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About the Company:Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!About the RoleAs an Agentic Product Analyst at Netomi, you will be the strategic and technical owner responsible for designing, architecting, and deploying large-scale Agentic AI solutions for enterprise customers. You will translate complex business processes into AI-driven workflows, define integration blueprints, and guide customers through their transformation to autonomous AI agents. You will work closely with Customers, CSM, Integration Engineers, QA, Product, and Engineering to ensure end-to-end success of every deployment.ResponsibilitiesLead discovery sessions with enterprise customers to understand business processes, operations, workflows, KPIs, and constraints.Identify automation opportunities and design agentic orchestration strategies using Netomi’s AI platform.Build detailed solution blueprints — workflows, data exchanges, escalation logic, guardrails, analytics, and agent lifecycle design.Define end-to-end Agentic AI architectures, covering intents, actions, tools, integration points, and decision logic.Work with customer technical teams to map integration dependencies (APIs, events, SSO, CRMs, ticketing systems, internal tools).Own the creation of integration design documents and support Integration Engineers during implementation.Ensure agent workflows comply with enterprise standards (security, reliability, audit, governance).Collaborate with Product & Engineering to translate customer requirements into features or enhancements.Serve as the product owner during deployment — driving priorities, clarifications, acceptance criteria, and workflow evolution.Validate solution behavior end-to-end with QA and guide test plans, scenario tests, and success criteria.Conduct user-experience reviews of agent outputs and behavior tuning.Act as a trusted advisor to customer stakeholders (CX, Ops, Digital Transformation, Engineering).Present architectural recommendations, best practices, and roadmap suggestions.Train customer teams on agentic workflows, governance, and performance improvement strategies.Ensure projects are delivered on time with high quality, low rework, and measurable impact.Drive continuous improvement through playbooks, reusable workflow templates, and integration patterns.Maintain deep expertise in agentic AI, LLMs, workflow orchestration, and enterprise systems.Requirements3–5 years in Solutions Architecture / Implementation Consulting / Product Consulting / Workflow Design for enterprise SaaS or AI platforms.Experience designing complex workflows and integrations across enterprise systems.Ability to gather requirements, translate them into technical specifications, and drive execution.Customer-facing consulting experience with strong communication & facilitation skills.Understanding of REST APIs, event-driven systems, data flows, and enterprise integrations.Experience working cross-functionally with CSM, engineering, product, and QA teams.Nice-to-HaveBackground in Conversational AI, Agentic AI, RPA, Automation, CRM/Ticketing, or LLM-based products.Hands-on experience defining business logic, decision trees, or automated workflows.Experience with enterprises such as airlines, BFSI, telecom, retail, or large-scale customer support environments.Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

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Why join us?Handoff is the AI agent that runs a construction company. We help remodelers automate estimating, streamline operations, and win more work - backed by real-time cost data, intuitive design, and workflows that “speak contractor.” With over 10,000 monthly active users and $6B in annualized project volume already flowing through our platform, we’re becoming the trusted partner for the people who build our homes.We are backed by $25M+ raised from Y Combinator, Initialized, and Greycroft. Our team is distributed across hubs in Austin, São Paulo, and Buenos Aires, and we are deeply focused on building intuitive, high-impact solutions that make a real difference for our users.Staff Machine Learning Engineer at HandoffAs a Staff engineer, you will focus primarily on GenAI and LLM-based systems, while maintaining a strong generalist foundation across machine learning, data, and production systems. This role is ideal for a highly experienced, hands-on engineer who thrives in ambiguous problem spaces and enjoys shaping technical direction through influence rather than formal management. Your impact will come from setting standards, unblocking complex problems, guiding architectural decisions, and elevating the overall quality and velocity of ML work across the team. What you'll doAct as a technical reference for the team, supporting engineers through design reviews, technical discussions, and hands-on problem-solving.Design, guide, and evolve LLM- and GenAI-based systems (e.g. AI agents, RAG pipelines, decision-support tools), balancing performance, cost, reliability, and user impact.Influence the architecture and implementation of ML systems across the stack, from data pipelines and experimentation to deployment and monitoring in production.Define and promote best practices and standards for model evaluation, experimentation, observability, and iteration across ML initiatives.Partner closely with product and engineering to shape ML-driven solutions, clarify trade-offs, and ensure alignment with business goals.Lead technically complex or ambiguous initiatives, unblocking teams and driving clarity where requirements or approaches are not well-defined.Improve the maturity of ML infrastructure and workflows to support multiple contributors and use cases over time.Stay up to date with advancements in GenAI, LLM tooling, and ML systems, selectively introducing new approaches where they provide clear value.Share knowledge through documentation, mentoring, and collaborative problem-solving, raising the technical bar across the organization.About youBachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience).8+ years of experience working with machine learning systems in production, with increasing technical scope and impact.Strong generalist ML background, with depth in modern GenAI and LLM-based systems.Comfortable operating in ambiguous environments, making sound technical decisions and clearly articulating trade-offs.Strong communicator who can translate complex technical concepts for engineers, product partners, and non-technical stakeholders.Product-minded, always grounding technical decisions in user value and business impact.Thrives in a fast-paced startup environment, balancing rapid iteration with long-term technical quality. Technical Expertise:Proficiency in foundational ML tools: Pandas, NumPy, OpenCV, and scikit-learn.Deep experience with LLMs and GenAI systems, including prompt engineering, RAG architectures, fine-tuning, evaluation, and cost/performance trade-offs.Hands-on experience with deep learning frameworks like PyTorch or TensorFlow.Experience designing, deploying, and maintaining production-grade ML systems on cloud platforms (AWS, GCP, or Azure).Strong understanding of data pipelines and ML workflows, using tools such as SQL, Apache Airflow, and cloud storage.Familiarity with computer vision techniques and tooling is a nice to have, but not required. If you enjoy shaping the technical direction of AI systems, tackling ambiguous problems, and using GenAI to deliver meaningful user and business impact, we’d love to hear from you!

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About the TeamThe Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-to-Market teams to inform high-stakes decisions through rigorous data science and economic modeling.As part of our expanding Data Science function, we’re building a best-in-class forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.We are developing a scalable forecasting platform to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy — supporting key investment decisions and unlocking OpenAI’s full potential.About the RoleWe’re looking for a hands-on technical leader to build and lead a small but mighty team of applied data scientists and ML engineers to develop forecasting capabilities and platforms from the ground up.Your team will be responsible for building and scaling robust, interpretable, and production-ready forecasting systems. These models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, compute consumption, and profitability.You will work closely with Strategic Finance leaders to integrate these scalable forecasting capabilities into their operational rhythms and collaborate with the Growth team to forecast key KPIs.This is a highly cross-functional role that requires technical excellence, strong product intuition, and business acumen. You’ll collaborate with various partners to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.This role is based in San Francisco, CA. We follow a hybrid work model of three days in the office per week and offer relocation assistance to new employees.In this role, you will:Build and manage a world-class team of applied data scientists and ML engineers to develop forecasting platforms at scale.Design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders.Collaborate closely with Strategic Finance teams to ensure forecasts are well integrated into planning processes, and executive decision-making.Work closely with cross-functional partners to help them adopt scientific, automated forecasting solutions.Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.Research and evaluate emerging tools and techniques in the forecasting space.Translate technical outputs into business-aligned recommendations and decision frameworks.You might thrive in this role if you have:Extensive experience building production-ready models for time series applications.Proven track record of building adjustable and explainable forecast models for multiple planning cycles.10+ years of applied data science & engineering experience, with deep hands-on expertise in forecasting and predictive modeling.Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.Excellent communication and storytelling skills — able to simplify complexity and influence executive stakeholders.Team leadership experience with a track record of building high-performing, engaged teams.An advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.The ability to thrive in a dynamic environment — flexible, resourceful, and willing to do what it takes to succeed.Experience building or scaling forecasting platforms in a high-growth company.A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments.Experience building or scaling forecasting platforms in a high-growth company.A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments. Bonus if you have:Experience building or scaling forecasting platforms in a high-growth company.A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Intrinsic is Alphabet’s bet aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core.  Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.Role As a Senior AI Research Scientist for Vision-guided robotics you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications.   How your work moves the mission forward Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.   Skills you will need to be successful PhD in Computer Science, Robotics, or a related field with a focus on machine learning or computer vision. 3 years of experience in applied research focused on robotic manipulation or robot learning. Proficiency in programming with Python and C++. Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Experience developing algorithms for vision-based manipulation or contact-rich interaction. Publication record in top-tier robotics or AI conferences (e.g., ICRA, IROS, CVPR, NeurIPS).    Skills that will differentiate your candidacy Experience with reinforcement learning or imitation learning for robotics. Familiarity with physics simulators like MuJoCo, Isaac Sim, or Gazebo. Experience integrating tactile sensors with visual perception systems Experience in LfD (Learning from Demonstrations), kinesthetic learning Background in sim-to-real transfer techniques for manipulation policies. Experience with transformer-based architectures or foundation models in a robotics context Experience deploying machine learning models on edge compute hardwar​e  At Intrinsic, we are proud to be an equal opportunity workplace. Employment at Intrinsic is based solely on a person's merit and qualifications directly related to professional competence. Intrinsic does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. It is Intrinsic’s policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. If you have a disability or special need that requires accommodation, please contact us at: candidate-support@intrinsic.ai.

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Intrinsic is Alphabet’s bet aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core.  Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.Role As a Senior AI Research Scientist for Vision-guided robotics you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications.   How your work moves the mission forward Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.   Skills you will need to be successful PhD in Computer Science, Robotics, or a related field with a focus on machine learning or computer vision. 3 years of experience in applied research focused on robotic manipulation or robot learning. Proficiency in programming with Python and C++. Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Experience developing algorithms for vision-based manipulation or contact-rich interaction. Publication record in top-tier robotics or AI conferences (e.g., ICRA, IROS, CVPR, NeurIPS).    Skills that will differentiate your candidacy Experience with reinforcement learning or imitation learning for robotics. Familiarity with physics simulators like MuJoCo, Isaac Sim, or Gazebo. Experience integrating tactile sensors with visual perception systems Experience in LfD (Learning from Demonstrations), kinesthetic learning Background in sim-to-real transfer techniques for manipulation policies. Experience with transformer-based architectures or foundation models in a robotics context Experience deploying machine learning models on edge compute hardwar​e  At Intrinsic, we are proud to be an equal opportunity workplace. Employment at Intrinsic is based solely on a person's merit and qualifications directly related to professional competence. Intrinsic does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. It is Intrinsic’s policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. If you have a disability or special need that requires accommodation, please contact us at: candidate-support@intrinsic.ai.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 700+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started. Role OverviewAs a Product Backend Engineer on Harvey’s product engineering team, you will design and operate the backend systems that turn cutting-edge AI capabilities into seamless, dependable product experiences. You’ll build secure, multi-tenant services, orchestrate interactions with LLMs and agentic tools, and help define the backend architecture that powers Harvey’s rapidly expanding product surface. Your work will have immediate business and customer impact as you ship the foundational systems behind our next generation of AI products.What You'll DoCollaborate closely with Product to prioritize customer-focused work and deliver reliable features quickly in a fast-moving environment.Design and own backend services and APIs that power Harvey’s web applications, workflows, and integrations.Model and manage data in Postgres and related data stores to support low-latency, reliable user experiences.Build secure, multi-tenant, permissions-aware systems with appropriate auditing for enterprise and government customers.Implement backend features and workflows that use LLMs and agentic tools, orchestrating calls to our AI systems from robust, well-structured services.Collaborate with frontend, product, and design partners to shape solutions, define clear API contracts, and ship features end-to-end.Add meaningful logging, metrics, and tracing so services are observable, debuggable, and ready for on-call ownership.Improve performance and scalability by profiling bottlenecks, tuning queries, and refining service boundaries as usage grows.Participate in code reviews, technical design discussions, and an on-call rotation for the services you own.What You Have5+ years of backend engineering experience building and operating production web applications or SaaS products.Track record of building fast-growing SaaS products by leveraging PWA technologiesTrack record of shipping highly intuitive products, strong attention to detailStrong programming skills in Python and experience with a modern web framework (e.g., FastAPI or Flask).Hands-on experience with relational databases (e.g., Postgres)Solid understanding of API design, authentication/authorization, background job patterns, and robust error handling.Experience building for Cloud Infrastructure such as Azure, AWS, or GCP.Comfort operating services in production using logs, metrics, dashboards, and alerts, including participation in an on-call rotation.#LI-KV1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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Intrinsic is Alphabet’s bet aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core.  Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.Role As a Senior AI Research Scientist for Vision-guided robotics you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications.   How your work moves the mission forward Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.   Skills you will need to be successful PhD in Computer Science, Robotics, or a related field with a focus on machine learning or computer vision. 3 years of experience in applied research focused on robotic manipulation or robot learning. Proficiency in programming with Python and C++. Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Experience developing algorithms for vision-based manipulation or contact-rich interaction. Publication record in top-tier robotics or AI conferences (e.g., ICRA, IROS, CVPR, NeurIPS).    Skills that will differentiate your candidacy Experience with reinforcement learning or imitation learning for robotics. Familiarity with physics simulators like MuJoCo, Isaac Sim, or Gazebo. Experience integrating tactile sensors with visual perception systems Experience in LfD (Learning from Demonstrations), kinesthetic learning Background in sim-to-real transfer techniques for manipulation policies. Experience with transformer-based architectures or foundation models in a robotics context Experience deploying machine learning models on edge compute hardwar​e  At Intrinsic, we are proud to be an equal opportunity workplace. Employment at Intrinsic is based solely on a person's merit and qualifications directly related to professional competence. Intrinsic does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. It is Intrinsic’s policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. If you have a disability or special need that requires accommodation, please contact us at: candidate-support@intrinsic.ai.

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Please read this firstWe know that this job title says we are looking for a Quantum Computing Researcher. In practice, this role is not that at all.We are using this title because people with backgrounds like yours tend to have the kind of brain that does exceptionally well here, even though the work itself does not fit neatly into an existing category.Maincode builds frontier AI models end to end. We design the models, run the infrastructure, and train on data we source and shape ourselves. What we have been calling a “data scientist” does not actually exist in the market in the form we need. The work we are doing is frontier work. It changes continuously as models, methods, and training regimes evolve, and there is no stable body of prior experience that reliably predicts success. This role is best understood internally as a Signal Engineer.What this role actually isThe real work here is not analytics, dashboards, or big data engineering.It is about how AI models learn, and specifically how the quality, composition, timing, and structure of input signal shapes learning outcomes across the full training lifecycle, from early pre training through mid training, post training, supervised fine tuning, and reinforcement learning.The analogy we use internally is a fuels engineer for a race car. The engine matters, but performance is ultimately unlocked by obsessing over the fuel. What goes in, how it is blended, when it is introduced, and how it changes under different conditions.What you would actually doYou would be responsible for designing, sourcing, shaping, and evaluating input signal at scale so that models learn faster, learn better, and generalize more effectively.This includes:Working deeply with raw and synthetic dataDesigning new datasets and signal mixturesIterating on input distributions and formatsUnderstanding how small changes in signal affect training behaviorThinking across stages of training, not in isolationTreating data as a dynamic, evolving system rather than a static assetThis is not about knowing the right answer up front. It is about immersion, experimentation, and developing intuition through long feedback loops.The kind of person who does well hereSuccess in this role is driven almost entirely by cognitive traits and working style, not prior AI experience.People who tend to thrive here:Have extreme attention to detail and care deeply about precisionAre comfortable with long arcs of repetitive, detailed workEnjoy staring at complex, noisy information until structure emergesAre excited by tuning, blending, and calibrating inputsHave high stamina and patienceLearn new technical domains very quickly when given dense materialGet intrinsic satisfaction from incremental improvement and deep understandingThese are people who do not get bored easily. They metabolize boredom into insight. They are depth driven rather than novelty driven.We explicitly do not require prior experience with large language models or modern AI training. No one meaningfully has that experience yet. What matters is learning gradient, range, and willingness to throw yourself into the problem space.How you would workYou would spend your time inside computational environments and technical tooling.You do not need to identify as a software engineer, but you should be comfortable:Working directly with data through scripts, notebooks, and experimental pipelinesModifying existing systems and building small utilities to explore questionsUsing code as a tool for thinking, testing, and refinementThe goal is speed of learning and depth of understanding, not polish.Backgrounds that often fit wellRather than advertising this role directly, we look for people in fields that reward signal sensitivity, precision, and long horizon reasoning.We expect to see strong candidates from areas such as:Actuarial scienceForensic accounting or forensic financeQuantum computingQuantitative risk modelingApplied statistics and signal processingEconometricsOperations researchWe also see excellent fits from applied mathematics, computational physics, systems engineering, bioinformatics, reliability engineering, and similar disciplines.Many people in these fields are constrained by conservative or slow moving industries and are actively looking for something more dynamic, even if they do not yet realize there is a place for them in frontier AI.How we interviewWe are explicitly hiring for learning gradient, not recall.Our process is designed to:See how quickly you build a mental model of an unfamiliar systemUnderstand how you reason about signal, feedback, and failure modesObserve how deeply you engage with input quality as a leverLearn whether you enjoy the work itself, not just the outcomeCorrectness matters less than depth, curiosity, and systems intuition.The core messageWe are offering a path for people who love signal, precision, and deep work to apply that obsession to frontier AI.This role is not about having the right background. It is about having the right brain, the right stamina, and the desire to become excellent at something that does not quite have a name yet.

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Please read this firstWe know that this job title says we are looking for an Actuary. In practice, this role is not that at all.We are using this title because people with backgrounds like yours tend to have the kind of brain that does exceptionally well here, even though the work itself does not fit neatly into an existing category.Maincode builds frontier AI models end to end. We design the models, run the infrastructure, and train on data we source and shape ourselves. What we have been calling a “data scientist” does not actually exist in the market in the form we need. The work we are doing is frontier work. It changes continuously as models, methods, and training regimes evolve, and there is no stable body of prior experience that reliably predicts success. This role is best understood internally as a Signal Engineer.What this role actually isThe real work here is not analytics, dashboards, or big data engineering.It is about how AI models learn, and specifically how the quality, composition, timing, and structure of input signal shapes learning outcomes across the full training lifecycle, from early pre training through mid training, post training, supervised fine tuning, and reinforcement learning.The analogy we use internally is a fuels engineer for a race car. The engine matters, but performance is ultimately unlocked by obsessing over the fuel. What goes in, how it is blended, when it is introduced, and how it changes under different conditions.What you would actually doYou would be responsible for designing, sourcing, shaping, and evaluating input signal at scale so that models learn faster, learn better, and generalize more effectively.This includes:Working deeply with raw and synthetic dataDesigning new datasets and signal mixturesIterating on input distributions and formatsUnderstanding how small changes in signal affect training behaviorThinking across stages of training, not in isolationTreating data as a dynamic, evolving system rather than a static assetThis is not about knowing the right answer up front. It is about immersion, experimentation, and developing intuition through long feedback loops.The kind of person who does well hereSuccess in this role is driven almost entirely by cognitive traits and working style, not prior AI experience.People who tend to thrive here:Have extreme attention to detail and care deeply about precisionAre comfortable with long arcs of repetitive, detailed workEnjoy staring at complex, noisy information until structure emergesAre excited by tuning, blending, and calibrating inputsHave high stamina and patienceLearn new technical domains very quickly when given dense materialGet intrinsic satisfaction from incremental improvement and deep understandingThese are people who do not get bored easily. They metabolize boredom into insight. They are depth driven rather than novelty driven.We explicitly do not require prior experience with large language models or modern AI training. No one meaningfully has that experience yet. What matters is learning gradient, range, and willingness to throw yourself into the problem space.How you would workYou would spend your time inside computational environments and technical tooling.You do not need to identify as a software engineer, but you should be comfortable:Working directly with data through scripts, notebooks, and experimental pipelinesModifying existing systems and building small utilities to explore questionsUsing code as a tool for thinking, testing, and refinementThe goal is speed of learning and depth of understanding, not polish.Backgrounds that often fit wellRather than advertising this role directly, we look for people in fields that reward signal sensitivity, precision, and long horizon reasoning.We expect to see strong candidates from areas such as:Actuarial scienceForensic accounting or forensic financeQuantum computingQuantitative risk modelingApplied statistics and signal processingEconometricsOperations researchWe also see excellent fits from applied mathematics, computational physics, systems engineering, bioinformatics, reliability engineering, and similar disciplines.Many people in these fields are constrained by conservative or slow moving industries and are actively looking for something more dynamic, even if they do not yet realize there is a place for them in frontier AI.How we interviewWe are explicitly hiring for learning gradient, not recall.Our process is designed to:See how quickly you build a mental model of an unfamiliar systemUnderstand how you reason about signal, feedback, and failure modesObserve how deeply you engage with input quality as a leverLearn whether you enjoy the work itself, not just the outcomeCorrectness matters less than depth, curiosity, and systems intuition.The core messageWe are offering a path for people who love signal, precision, and deep work to apply that obsession to frontier AI.This role is not about having the right background. It is about having the right brain, the right stamina, and the desire to become excellent at something that does not quite have a name yet.

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At Replicant, we believe AI should work for people, starting with customer service. That’s why we built a platform that helps contact centers resolve more requests, proactively identify issues, and improve agent performance with AI-powered conversation intelligence and AI agents that act like your best reps.Our AI agents handle millions of calls every month for Fortune 500 companies and high-growth innovators. From processing payments to booking appointments and authenticating users, they help customers get what they need instantly, 24/7. Meanwhile, our real-time conversation insights help contact center leaders coach better and improve every interaction.We’re leading the shift from legacy systems to AI-first service, powered by large language models (LLMs) and designed for enterprise scale, security, and empathy. If you’re excited by the potential of LLMs, voice AI, and building category-defining technology with a kind, ambitious team, you’ll love it here.We're looking for a Principal Product Manager to shape the future of autonomous customer service at the intersection of AI research and enterprise product development. You'll take ownership of large, ambiguous, and unexplored problems—defining Replicant's long-term product and AI strategy while driving execution across multiple teams. This is a role for someone who can think at the frontier of what's possible with LLMs, translate that into products that deliver measurable enterprise value, and inspire teams to build what hasn't been built before.What You'll DoDefine and drive multi-team product and AI strategy that shapes Replicant's vision for the next generation of AI customer service. Own problems at the product and company strategy level, balancing long-term technical bets with iterative delivery.Stay at the frontier of AI capabilities—deeply understand the evolving landscape of large language models, voice AI, evaluation frameworks, and agentic architectures. Determine where Replicant should build, partner, or integrate to maintain a technical and strategic edge.Lead cross-functional initiatives with measurable business and customer impact. Own roadmaps from conception through execution and iteration, working across AI/ML, engineering, design, and go-to-market teams.Drive customer and market research in uncharted areas. Regularly engage with customers, prospects, and industry leaders (2-3+ interactions per week) to gather signal on complex, multi-team problems. Share insights that shape product strategy across the organization.Establish and own company-wide product metrics—including accuracy, containment, task success rates, latency, CSAT, and cost efficiency—and use them to guide decisions at the strategic level.Communicate and inspire across all audiences—from engineering teams to executives, board, and customers. Tell stories that align the company and close enterprise deals. Regularly represent EPD and Replicant externally.Coach and elevate the product team. Lead through example, provide regular feedback, and make everyone around you a better PM. Drive hiring for senior and executive positions, closing top candidates.What You'll Bring8+ years of product management experience, with significant time spent on AI/ML products, voice AI, conversational AI, or technically complex enterprise platforms.Deep technical fluency in AI/ML—you understand how LLMs work, can reason about model capabilities and limitations, and have an informed opinion on architecture decisions and their long-term roadmap implications. Experience with prompt engineering, RAG, fine-tuning, or AI agent development is a strong plus.Track record of owning large, ambiguous, complex problems and driving them to successful outcomes across multiple teams. You bring clarity to chaos and create alignment where none exists.Demonstrable success building AI-powered products that shipped to production and delivered measurable customer value. You've seen what works and what doesn't when translating AI capabilities into enterprise-grade products.Exceptional communication and storytelling skills—you can explain complex AI concepts to any audience, facilitate large groups, and craft narratives that inspire customers, teams, and executives.Strong quantitative skills—comfortable using complex data analysis to make decisions, publishing results and dashboards, and leading creation of metrics that measure company-wide strategy.Experience working directly with customers to understand requirements, present product vision, and serve as a strategic advisor. You've influenced enterprise deals and shaped products based on deep customer insight.Comfort operating at the frontier—you thrive in fast-paced, evolving environments where the technology itself is changing rapidly. You adapt as customer needs, AI capabilities, and priorities shift.Nice to HaveExperience with voice AI, speech recognition, or real-time conversational systemsBackground in contact center technology, customer service platforms, or B2B SaaSCoding proficiency sufficient to build prototypes, review technical designs, or engage deeply with engineering trade-offsMBA or equivalent business experienceFor all full-time employees, we offer:🌴 In-person connection that counts: company-wide offsites and smaller team gatherings designed to make remote work feel personal🖥️ Tech & learning stipend: Conferences, books, courses — interested? We’ll fund them📍 Remote by design: We’re distributed — no guilt about life events, we trust you to manage your calendar🏋️ Health & wellness: Flexible vacations, paid sabbatical after 5 years, comprehensive benefits, plus a stipend to support your physical and mental well-being💸 Compensation that matches your impact: competitive salaries in the company you’re helping to build📈 Equity with upside: We believe in shared ownership—You’ll own a real piece of a fast-growing AI companyOur ValuesReplicant has three core values. It is critical that everyone who joins the team feels excited and moved by these values as every new team member makes an impact on our culture.Blade Runners: We take ownership and pride to influence the outcomes of our goals. We are successful, and like a Blade Runner, use the tools at our disposal to reach our objectives. We value open and honest communication and proactively seek feedback along the way. We are a company driven to grow and achieve both individually and as a team.Bread Makers: We are humble and strive toward an egalitarian culture. No task is too big or too small. We work together to achieve our goals and develop our company mission. We believe that the whole is greater than the sum of its parts in everything that we do.Självdistans (Self-Distance): Självdistans is Swedish for self-distance. It's the ability to critically reflect on oneself and one's relations from an external perspective. With this in mind, we act with objectivity and always remember that we are not our work. There's no perfect science to growing a team or business, but we trust everyone at Replicant to point out our blind spots and humbly admit their own.Replicant is proud to be an equal opportunity employer. We are committed to fostering an inclusive, diverse and equitable workplace that is built on trust, support and respect. We welcome all individuals and do not discriminate on the basis of gender identity and expression, race, ethnicity, disability, sexual orientation, colour, religion, creed, gender, national origin, age, marital status, pregnancy, sex, citizenship, education, languages spoken or veteran status. Accommodation is available upon request at any point during our recruitment process. If you require an accommodation, please speak to your talent acquisition partner or email us at talent@replicant.ai and we’ll work to meet your needs.

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About the Team The Knowledge Innovation team is scaling OpenAI with OpenAI. We are building a model powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for a Backend Software Engineer to help architect and scale the infrastructure that powers our knowledge systems. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. In this role, you will:Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systemsIntegrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows.Collaborate closely with product, research, and engineering teams to integrate OpenAI models into high-leverage workflowsOwn the full development lifecycle of new backend systems and internal platform capabilitiesBuild with scale and maintainability in mind, while rapidly iterating on new ideas You might be a great fit if you have:4+ years of backend engineering experience at product-driven companies (excluding internships)Proficiency in backend technologies. Our tech stack includes Python, FastAPI, and PostgresExperience designing and scaling distributed systems, APIs, or data processing pipelinesA pragmatic mindset. You’re comfortable shipping iteratively while building toward a long-term visionAn interest in structured knowledge representation, internal search, agent infrastructure, or systems that evolve over time Curiosity about AI/ML and excitement to work alongside world-class research and product teams (hands-on experience is a bonus, not a must)About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Intrinsic is Alphabet’s bet aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core.  Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.Role As a Senior AI Research Scientist for Vision-guided robotics you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications.   How your work moves the mission forward Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.   Skills you will need to be successful PhD in Computer Science, Robotics, or a related field with a focus on machine learning or computer vision. 3 years of experience in applied research focused on robotic manipulation or robot learning. Proficiency in programming with Python and C++. Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Experience developing algorithms for vision-based manipulation or contact-rich interaction. Publication record in top-tier robotics or AI conferences (e.g., ICRA, IROS, CVPR, NeurIPS).    Skills that will differentiate your candidacy Experience with reinforcement learning or imitation learning for robotics. Familiarity with physics simulators like MuJoCo, Isaac Sim, or Gazebo. Experience integrating tactile sensors with visual perception systems Experience in LfD (Learning from Demonstrations), kinesthetic learning Background in sim-to-real transfer techniques for manipulation policies. Experience with transformer-based architectures or foundation models in a robotics context Experience deploying machine learning models on edge compute hardwar​e  At Intrinsic, we are proud to be an equal opportunity workplace. Employment at Intrinsic is based solely on a person's merit and qualifications directly related to professional competence. Intrinsic does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. It is Intrinsic’s policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. If you have a disability or special need that requires accommodation, please contact us at: candidate-support@intrinsic.ai.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking for:We’re looking for curious and intellectually proactive contributors, the kind of person who double-checks assumptions and plays devil’s advocate. Are you comfortable with ambiguity and complexity? Does an async, remote, flexible opportunity sound exciting? Would you like to learn how modern AI systems are tested and evaluated?This is a flexible, project-based opportunity well-suited for:Analysts, researchers, or consultants with strong critical thinking skills.Students (senior undergrads / grad students) looking for an intellectually interesting gig.People open to a part-time and non-permanent opportunity. About the project:We’re on the hunt for QAs for autonomous AI agents for a new project focused on validating and improving complex task structures, policy logic, and agent evaluation frameworks. Throughout the project, you’ll have to balance quality assurance, research, and logical problem-solving. This project opportunity is ideal for people who enjoy looking at systems holistically and thinking through scenarios, implications, and edge cases.You do not need a coding background, but you must be curious, intellectually rigorous, and capable of evaluating the soundness and consistency of complex setups. If you’ve ever excelled in things like consulting, CHGK, Olympiads, case solving, or systems thinking — you might be a great fit.What you’ll be doing:Reviewing evaluation tasks and scenarios for logic, completeness, and realism.Identifying inconsistencies, missing assumptions, or unclear decision points.Helping define clear expected behaviors (gold standards) for AI agents.Annotating cause-effect relationships, reasoning paths, and plausible alternatives.Thinking through complex systems and policies as a human would to ensure agents are tested properly.Working closely with QA, writers, or developers to suggest refinements or edge case coverage.How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsExcellent analytical thinking: Can reason about complex systems, scenarios, and logical implications.Strong attention to detail: Can spot contradictions, ambiguities, and vague requirements.Familiarity with structured data formats: Can read, not necessarily write JSON/YAML.Ability to assess scenarios holistically: What's missing, what’s unrealistic, what might break?Good communication and clear writing (in English) to document your findings. We also value applicants who have:Experience with policy evaluation, logic puzzles, case studies, or structured scenario design.Background in consulting, academia, olympiads (e.g. logic/math/informatics), or research.Exposure to LLMs, prompt engineering, or AI-generated content.Familiarity with QA or test-case thinking (edge cases, failure modes, “what could go wrong”).Some understanding of how scoring or evaluation works in agent testing (precision, coverage, etc.).BenefitsGet paid for your expertise, with rates that can go up to $80/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking for:We’re looking for curious and intellectually proactive contributors, the kind of person who double-checks assumptions and plays devil’s advocate. Are you comfortable with ambiguity and complexity? Does an async, remote, flexible opportunity sound exciting? Would you like to learn how modern AI systems are tested and evaluated?This is a flexible, project-based opportunity well-suited for:Analysts, researchers, or consultants with strong critical thinking skills.Students (senior undergrads / grad students) looking for an intellectually interesting gig.People open to a part-time and non-permanent opportunity. About the project:We’re on the hunt for QAs for autonomous AI agents for a new project focused on validating and improving complex task structures, policy logic, and agent evaluation frameworks. Throughout the project, you’ll have to balance quality assurance, research, and logical problem-solving. This project opportunity is ideal for people who enjoy looking at systems holistically and thinking through scenarios, implications, and edge cases.You do not need a coding background, but you must be curious, intellectually rigorous, and capable of evaluating the soundness and consistency of complex setups. If you’ve ever excelled in things like consulting, CHGK, Olympiads, case solving, or systems thinking — you might be a great fit.What you’ll be doing:Reviewing evaluation tasks and scenarios for logic, completeness, and realism.Identifying inconsistencies, missing assumptions, or unclear decision points.Helping define clear expected behaviors (gold standards) for AI agents.Annotating cause-effect relationships, reasoning paths, and plausible alternatives.Thinking through complex systems and policies as a human would to ensure agents are tested properly.Working closely with QA, writers, or developers to suggest refinements or edge case coverage.How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsExcellent analytical thinking: Can reason about complex systems, scenarios, and logical implications.Strong attention to detail: Can spot contradictions, ambiguities, and vague requirements.Familiarity with structured data formats: Can read, not necessarily write JSON/YAML.Ability to assess scenarios holistically: What's missing, what’s unrealistic, what might break?Good communication and clear writing (in English) to document your findings. We also value applicants who have:Experience with policy evaluation, logic puzzles, case studies, or structured scenario design.Background in consulting, academia, olympiads (e.g. logic/math/informatics), or research.Exposure to LLMs, prompt engineering, or AI-generated content.Familiarity with QA or test-case thinking (edge cases, failure modes, “what could go wrong”).Some understanding of how scoring or evaluation works in agent testing (precision, coverage, etc.).BenefitsGet paid for your expertise, with rates that can go up to $80/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.