AI Product & Operation Jobs

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The Company   Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.   The Role Metropolis is seeking a Senior Machine Learning Software Engineer to accelerate the development of our proprietary computer vision and machine learning software that powers our mobility products.  As part of the Metropolis Machine Learning Team, you will be responsible for the development, deployment, and ongoing optimization of edge-deployed software. These systems are foundational to the Metropolis platform and have correspondingly large potential impacts on Metropolis and its customers.  You will find this to be a challenging opportunity filled with unique technical and operational considerations while being able to learn from and leverage our existing Computer Vision based development and operational ecosystem.  The right candidate will possess a strong background in C++ and OpenCV, experience with computer vision and ML on edge / embedded systems, and demonstrated experience taking complex software systems from concept to production.  You can expect to be working on all stages of the software development pipeline – from problem analysis and design to prototyping and deployment.  You should be able to thrive and succeed in an entrepreneurial setting, working collaboratively in a fast-paced environment with multiple stakeholders.  You won’t be afraid to break new technological ground at Metropolis and are more than willing to roll up your sleeves, dig in and get the job done.   Responsibilities Work with the Machine Learning Team to design, develop, improve, and optimize computer vision, machine learning and application software on edge devices using C++.  Participate in all phases of embedded software development, from concept and design to deployment and maintenance.  Identify top-level software requirements and establish development best practices.  Deliver high-quality C++ code in a real-time embedded environment.  Perform optimization on Machine Learning models targeting different hardware accelerators e.g. CUDA cores, Qualcomm DSP, etc.  Implement, manage, and support over-the-air software updates to edge systems.  Communicate ideas and results effectively, verbally and in writing, to a wide range of technical and non-technical audiences.    Qualifications  BS, MS, or Ph.D. in a Computer Science and Engineering or relevant discipline.  5+ years experience in modern software design, development, version control, refactoring, and testing  5+ years of experience with C++17 onward and a strong understanding of object-oriented programming  3+ years of experience working with C++ OpenCV, SQLLite and MQTT.  Experience in parallel computing, accelerator architecture, CUDA, Qualcomm DSP, and TensorRT libraries.  Experience with ARM Cortex series microcontroller  Excellent written and verbal communication skills with a proven ability to present complex technical information in a clear and concise manner to a variety of audiences  Previous experience working inside innovative, high-growth environments  Strong preference for candidates to be local to the Seattle area. Will also consider candidates in Los Angeles, Seattle, and New York.   When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 to $200,000.00 annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more.  #LI-AR1 #LI-Onsite Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.  

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The Company   Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.   The Role Metropolis is seeking a Senior Machine Learning Software Engineer to accelerate the development of our proprietary computer vision and machine learning software that powers our mobility products.  As part of the Metropolis Machine Learning Team, you will be responsible for the development, deployment, and ongoing optimization of edge-deployed software. These systems are foundational to the Metropolis platform and have correspondingly large potential impacts on Metropolis and its customers.  You will find this to be a challenging opportunity filled with unique technical and operational considerations while being able to learn from and leverage our existing Computer Vision based development and operational ecosystem.  The right candidate will possess a strong background in C++ and OpenCV, experience with computer vision and ML on edge / embedded systems, and demonstrated experience taking complex software systems from concept to production.  You can expect to be working on all stages of the software development pipeline – from problem analysis and design to prototyping and deployment.  You should be able to thrive and succeed in an entrepreneurial setting, working collaboratively in a fast-paced environment with multiple stakeholders.  You won’t be afraid to break new technological ground at Metropolis and are more than willing to roll up your sleeves, dig in and get the job done.   Responsibilities Work with the Machine Learning Team to design, develop, improve, and optimize computer vision, machine learning and application software on edge devices using C++.  Participate in all phases of embedded software development, from concept and design to deployment and maintenance.  Identify top-level software requirements and establish development best practices.  Deliver high-quality C++ code in a real-time embedded environment.  Perform optimization on Machine Learning models targeting different hardware accelerators e.g. CUDA cores, Qualcomm DSP, etc.  Implement, manage, and support over-the-air software updates to edge systems.  Communicate ideas and results effectively, verbally and in writing, to a wide range of technical and non-technical audiences.    Qualifications  BS, MS, or Ph.D. in a Computer Science and Engineering or relevant discipline.  5+ years experience in modern software design, development, version control, refactoring, and testing  5+ years of experience with C++17 onward and a strong understanding of object-oriented programming  3+ years of experience working with C++ OpenCV, SQLLite and MQTT.  Experience in parallel computing, accelerator architecture, CUDA, Qualcomm DSP, and TensorRT libraries.  Experience with ARM Cortex series microcontroller  Excellent written and verbal communication skills with a proven ability to present complex technical information in a clear and concise manner to a variety of audiences  Previous experience working inside innovative, high-growth environments  Strong preference for candidates to be local to the Seattle area. Will also consider candidates in Los Angeles, Seattle, and New York.   When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 to $200,000.00 annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more.  #LI-AR1 #LI-Onsite Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.  

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Who We Are  PathAI is on a mission to improve patient outcomes with AI-powered pathology. We are transforming traditional pathology methods into powerful, new technologies. These innovations in pathology can help accelerate drug development, improve confidence in the accuracy of diagnosis, and get life-saving therapies to patients more quickly. At PathAI, you'll work with a diverse and talented team of people, who are dedicated to solving complex problems and making a huge impact. Where You Fit You’ll work closely with our development squads while helping to lead and coordinate the efforts of our SDET team. As a key point of contact between engineering and quality, you’ll bring visibility to testing activities, drive process improvements, and ensure that quality remains a priority throughout the development lifecycle. This role is ideal for someone who’s hands-on, collaborative, and ready to take ownership of how we build and verify great products. What You’ll Do  Take ownership of quality assurance processes across multiple development squads Collaborate closely with engineering leadership and product teams to align on quality goals Track development progress and manage the QA testing backlog Write and maintain manual test cases for new and existing features when needed Support test automation by providing test data, building fixtures, and running exploratory tests Oversee the verification process, including documentation updates and compliance activities Maintain end-to-end test traceability from requirements through test execution Monitor CI/CD pipelines, investigate failures, and communicate issues to the engineering team Represent the SDET team in squad meetings and share quality status, risks, and metrics Work from our office in Boston (2+ days/week in office if local) or remotely from the United States on Eastern or Central hours) What You Bring Strong organizational skills and attention to detail Clear and effective communication, both written and verbal Ability to quickly learn and adapt in a fast-paced environment 1-2 years programming experience (e.g., Python or TypeScript) Understanding of test automation concepts Familiarity with modern testing frameworks such as Playwright or Cypress Experience with CI/CD tools like GitLab, GitHub Actions, or CircleCI Experience with Jira for test and issue tracking Background in Agile or Scrum development environments A collaborative mindset and a proactive approach to solving problems Nice to have: Experience in regulated industries (e.g., medical devices, finance, aerospace) Familiarity with advanced test management tools (e.g., Xray, Zephyr) We Want to Hear From You At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for.  PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way.  #LI-Remote

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This role is remote and can be executed globally. If you prefer, you can work from our offices in Bangalore, Dublin, London, New York, San Francisco, Tokyo, and Warsaw.About ElevenLabsElevenLabs is a research and product company defining the frontier of Audio AI. Millions of individuals use ElevenLabs to read articles, voice over their videos, and reclaim voices lost from disability. And the leading developers and enterprises use ElevenLabs to create Conversational AI agents for support, sales, and education.ElevenLabs launched in January 2023 with the first AI model to cross the threshold of human-like speech. In January 2025, we raised a $180 million Series C round, valuing ElevenLabs at $3.3 billion. The round was co-led by Andreessen Horowitz and ICONIQ Growth, with continued support from the leading names in tech, including Nat Friedman, Daniel Gross, Instagram co-founder Mike Krieger, Oculus VR co-founder Brendan Iribe, DeepMind and Inflection co-founder Mustafa Suleyman, and many others.ElevenLabs is only 2 years old and scaling rapidly. We are just getting started. If you want to work hard and have an incredible impact, we would love to hear from you.How we workHigh-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.Excellence everywhere: Everything we do should match the quality of our AI models.Global team: We prioritize your talent, not your location. What we offerLearning & development: Annual discretionary stipend towards professional development. Social travel: Annual discretionary stipend to meet up with colleagues each year, however you choose.Annual company offsite: We bring the entire company together at a new location every year.Co-working: If you’re not located near one of our main hubs, we offer a monthly coworking stipend.About the roleWe’re hiring a Developer Relations Engineer. In this role, you’ll play a core part in improving our developer experience — particularly our documentation and example projects. You’ll dive deep into where users are getting stuck and ship what they need to succeed.You’ll also help drive acquisition of our technical, self-serve customers by creating and presenting engaging content online and in-person — especially at developer meetups and conferences across the US, with a focus on events in the San Francisco Bay Area.This role is perfect for someone who can create compelling technical content and is energized by connecting with developers face-to-face.RequirementsYou love attending, organizing, and speaking at developer events.You're able to tailor messaging for different audiences and build strong networks with developers, startup accelerators, and VCs alike.A strong full-stack engineering skillset with an eye for design — bonus points if you leverage new AI coding tools.The ability to come up with great ideas for tutorials, build working demos, and create high-quality blog posts and talks.A passion for writing engaging technical content.A product-minded approach to content: you understand metrics, speak to users, decide what to build/write based on needs, and double down on what works.#LI-Remote

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Join Our Mission to Revolutionize Healthcare Thoughtful is pioneering a new approach to automation for all healthcare providers! Our AI-powered Revenue Cycle Automation platform enables the healthcare industry to automate and improve its core business operations. We’re hiring a Senior Security Engineer to secure and scale our stack. You’ll own platform security, system reliability, audit readiness, and integration strategy across cloud and hybrid environments.  You'll take ownership of system reliability, security posture, audit readiness, and help guide our long-term integration strategy across cloud and legacy environments. We're unifying cloud-native and legacy systems into a secure, high-availability platform that powers AI-driven automation across healthcare. You’ll lead foundational work in infrastructure hardening, audit controls, and production observability, directly supporting mission-critical AI agents. You'll have executive support and budget to modernize everything from our VPN tunnels to our alerting stack. What You’ll Own: Integration Strategy: Lead infrastructure and tooling decisions as we unify multiple environments into a single, scalable platform. Audit Readiness: Own and drive SOC 2 Type II and HITRUST prep, working across engineering, compliance, and security. System Reliability: Ensure uptime, scalability, and fault tolerance across services. Set and enforce SLAs. On-Call Infrastructure: Stand up our alerting, escalation, and incident response systems. Observability: Improve logging, metrics, and dashboards using tools like HyperDX. Infrastructure Provisioning: Spin up and manage production-grade infrastructure using OpenTofu/Terraform. Security & Networking: Architect infrastructure with security best practices, including VPNs, IPsec tunnels, and hybrid network topologies. Your Qualifications: 8+ years of experience spanning Security, DevOps, and/or SRE roles in high-availability, cloud and hybrid environments—with a strong track record of leading integrations, hardening infrastructure, and ensuring audit/compliance readiness. Start-up mentality - desire to tackle ambiguous scope of work and willing to do whatever is necessary to drive the company/mission forward. Track record leading complex infrastructure integrations Deep AWS expertise; strong experience with Azure and/or GCP a bonus Proficiency in OpenTofu or Terraform for Infrastructure-as-Code Comfortable navigating hybrid cloud environments (e.g. EKS, legacy VMs, VPN tunnels) Solid Kubernetes experience (Knative experience a plus) Strong networking fundamentals and experience with on-prem systems Familiar with incident tooling (PagerDuty, Opsgenie) and setting SLOs/SLAs Personable and cross-functional: able to build rapport with stakeholders across engineering, compliance, and executive leadership Security-first mindset, with an eye for compliance and audit readiness Proficiency in SOC2 Type 2, HITRUST preparation. Comfortable spinning up new infrastructure as needed What Sets You Apart: You've integrated cutting edge cloud environments with customer's legacy environments You’ve built platforms, not just maintained them You treat DevOps as a product, not just a support function You care about developer experience, observability, and operational excellence   Why Thoughtful? Competitive compensation Equity participation: Employee Stock Options. Health benefits: Comprehensive medical, dental, and vision insurance. Time off: Generous leave policies and paid company holidays.  California Salary Range $170,000—$220,000 USD

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About Faculty At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.About the roleThis is an exciting opportunity to join Faculty as the most senior data scientist in its recently formed Professional and Financial Services Team. As the Lead Data Scientist, you’ll have an opportunity to shape a technical vision and guide the senior and junior data scientists on your team. Working collaboratively, you will oversee project teams that deliver high-impact AI solutions that are differentiated and compelling. You will also lead project teams delivering enterprise-scale applications for a range of clients, including major banks, asset managers, insurers, law firms, and B2B services.Maintaining ownership of the data science approach, you will own the technical vision for your projects, partner directly with clients to shape strategy, and play a crucial part in mentoring the next generation of data science talent at Faculty.What you'll be doingProject Leadership:Guide the technical delivery of custom data science solutions for clients, from initial discovery to deployment in productionOwn the end-to-end data science approach, designing and implementing the appropriate techniques - from classic to AI agents using LLMs - that are designed, optimised and applied at scaleDesign robust and scalable software architecture for the solutions you build, ensuring best practices in engineering and MLOps are followed.Partner with our commercial team and clients to build strong relationships, acting as a trusted technical advisor.Articulate intricate technical concepts and strategic decisions clearly and effectively to diverse audiences, from client-side engineers to C-suite executives.Team Mentorship:Formally manage and mentor a number of data scientists, taking responsibility for their career progression and professional growth.Provide targeted technical support and learning opportunities for data scientists on your project teams.Contribute to sustaining our culture, creating an atmosphere of collaboration and setting a high standard for performance and technical excellence.Technical LeadershipEstablish a distinct and differentiated data science vision for professional and financial services, and communicate that vision through external thought leadership and in potential client presentations.Partner with our commercial team to ensure potential projects and programmes of work are appropriately resourced, balancing client delivery, colleague wellbeing, and commercial imperatives.Keep abreast of the latest technical and technology advancements, share these with others in the organisation, and identify how they can help drive Faculty forward.Who we're looking forYou have deep technical expertise in machine learning and a command of diverse methodologies, with a solid grasp of data science and statistical techniques, for example: supervised/unsupervised machine learning, model cross-validation, Bayesian inference, and time-series analysisAn excellent proficiency of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch)Demonstrable experience enabling impactful change with AI within a financial services institution. Coupling that with prior experience in consulting would be a bonus.You possess proven experience leading data science projects and making key decisions on technical direction and architecture.You are an exceptional communicator, capable of building rapport with clients and translating complex ideas into clear, actionable insights.You have a strategic mindset, with a grasp on key financial services sector trends that informs a compelling technical vision.You are passionate about developing people and have experience mentoring or managing other technical professionals.You are motivated to contribute to the wider data science community. We will actively support you in building your professional profile by speaking at major conferences, delivering courses, or contributing to open-source projects.What we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.

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About KreaAt Krea, we are building next-generation AI creative tools.We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium.This jobRobust, reliable, and scalable distributed systems form the backbone of Krea. These systems support the infrastructure that powers our AI research, real-time user experiences, and large-scale model deployments.As a Distributed Systems Engineer, you will…… design, build, and maintain large-scale distributed infrastructure to reliably support AI research and real-time model serving.… own and scale our multi-thousand-node Kubernetes GPU clusters, ensuring efficient and fault-tolerant operations.… collaborate closely with ML engineers and researchers to architect systems that enable rapid experimentation and deployment.… improve network architecture, optimize load balancing, and streamline operational practices across multi-zone cloud deployments.Example projectsOwn and manage a large-scale Kubernetes cluster designed to run extensive ML training and inference workloads.Architect fault-tolerant systems ensuring uninterrupted model training and real-time inference despite individual node failures.Develop and implement optimized load-balancing strategies to efficiently distribute workloads across zones.Create comprehensive monitoring, alerting systems, and operational playbooks for high-availability clusters.Migrate existing deployments to Infrastructure as Code (Terraform) for reproducibility and scalability.Setting up IP-based rate-limiting to prevent GPU abuse.Strong candidates may have experience with…Kubernetes at scale (thousands of nodes)Cloud infrastructure management (AWS/GCP/Azure)High-performance and fault-tolerant networkingLow-level Linux interfaces and administrationDebugging complex distributed systems in productionPython, Golang, Ruby, Rust, and similar systems languagesBonus: Infrastructure as Code (e.g. Terraform)About usWe’re building AI creative tooling.We’ve raised over $83M from the best investors in Silicon Valley.We’re a team of 12 with millions of active users scaling aggressively.

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About KreaAt Krea, we are building next-generation AI creative tools.We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium. This jobWe're looking for a machine learning engineers who can work on large-scale image and video models training experiments..Some stuff you can do:Train foundation diffusion models for image and video generation.Train controllability modules such as IPAdapters or ControlNets.Develop novel research techniques and put them into production.Conducting large-scale experiments on high-performance computing clusters, optimizing data pipelines for massive image datasetsExample experience and skills we’re looking forProven track record in working with image or video models at scale (publications or open-source contributions a plus)Strong background in deep learning frameworks and distributed training paradigms.Ability to iterate rapidly, and propose creative research directionsA bit more about usWe’ve raised over $83M and are backed by world-class Silicon Valley investors such as Andreessen Horiwitz, and the cofounder of the Meta AI Research laboratory (FMK as Facebook AI Research) or founding members of OpenAI.

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About KreaAt Krea, we are building next-generation AI creative tools.We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium. Some examples of things you will do:Build and maintain APIs and UI flows for web + mobile in Svelte/SvelteKit, TypeScript.Design interactive, responsive front-end experiences—drag-and-drop, real-time canvas polish, smooth and responsive UI animations.Optimize frontend performance: minimize render latency, profile UI with virtual DOM techniques, deliver seamless WebSocket image streams.Design and maintain backend services (Node), DB models (Postgres + Redis caching/pooling).Kickstart a Public API project to serve Krea AI models to millions of developers.Diagnose HTTP/3 and WebSocket related issues both on the client side and the server side.Drive real-time image & video generation pipelines via low-latency APIs.Improve observability and alerting using OpenTelemetry tools.Implement enterprise features: Audit Logs, SAML/SSO, SCIM provisioning.Bonus: Scale our infra architecture through deep understanding of our AWS EKS GPU clusters or Kubernetes operators.Strong candidates may have experience with the following:Solid full-stack JS/TS engineer with frontend focus—component design, UI state, animations, client performance.Experience with SvelteKit or similar frameworks, real-time UI via WebSockets.Comfortable designing APIs, database schemas, caching strategies.Familiar with infra and scale: Kubernetes, Postgres, Redis, observability stacks.Side projects or open‑source contributions in UI/infra are plus.Bonus: prior work on enterprise auth features, GPU workloads, ML or image/video pipelines.Stack:Frontend: Svelte/SvelteKitBackend: Node + TypeScript, Postgres, RedisRealtime: WebSockets, HTTP/3Infra: AWS EKS GPU clusters, KubernetesObservability: Prometheus, OpenTelemetry, Axiom/HyperDXTools: GitHub, Slack, Notion

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About KreaAt Krea, we are building next-generation AI creative tools.We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium. What you'll doDesign, implement, deploy, and maintain private APIs for our main web and mobile applications.Design database models.Fix issues with our system that, among other things, may be related to how HTTP/3 handles client-side connections to our processes.Improve database and infrastructure performance by implementing caching solutions or better connection pooling.Profile and find bottlenecks for many types of HTTP/WebSockets requests to enable real-time image generation—and even video!Improve observability, monitoring, and alerting for our service so that we can better respond to operational incidentsScale our service via architectural changes as well as infrastructure improvementsOpen-source any non-trivial innovations that come out of our work on the productDesign and iterate over software development processes so that we can build an web-native and AI-native creative tools for people.Professionalize our main product by adding enterprise-grade features such as Audit Logs, SAML/SSO, SCIM.Our stackJavascript/TypeScriptSvelte & SvelteKitNode, Postgres, and RedisWebSocketsManaged Kubernetes cluster(s) on AWSMonitored and observed via Axiom/HyperDX/Prometheus/OpenTelemetryGitHub, Slack, Notion

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About KreaAt Krea, we are building next-generation AI creative tools.We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium. This jobData is one of the fundamental pieces of Krea. Huge amounts of data power our AI training pipelines, our analytics and observability, and many of the core systems that make Krea tick.As a data engineer, you will…… build distributed systems to process gigantic (petabytes) amounts of files of all kinds (images, video, and even 3D data). You should feel comfortable solving scaling problems as you go.… work closely with our research team to build ML pipelines and deploy models to make sense of raw data.… play with massive amounts of compute on huge kubernetes GPU clusters - our main GPU cluster takes up an entire datacenter from our provider.… learn machine learning engineering (ML experience is a bonus, but you can also learn it on the job) from world-class researchers on a small yet highly effective tight-knit team.Example projectsFind clean scenes in millions of videos, running distributed data pipelines that detect shot boundaries and saving timestamps of clips.Solve orchestration and scaling issues with a large-scale distributed GPU job processing system on kubernetess.Build systems to deploy and combine different LLMs to caption massive amounts of multimedia data in a variety of different ways.Design multi-stage pipelines to turn petabytes of raw data into clean downstream datasets, with metadata, annotations, and filters.Strong candidates may have experience with…Python, PyArrow, DuckDB, SQL, massive relational databases, PyTorch, Pandas, NumPy…KubernetesDesigning and implementing large-scale ETL systemsFundamental knowledge of containerization, operating systems, file-systems, and networking.Distributed systems designAbout usWe’re building AI creative tooling.We’ve raised over $83M from the best investors in Silicon Valley.We’re a team of 12 with millions of active users scaling aggressively.

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About GPTZeroGPTZero is on a mission to restore trust and transparency on the internet. As the leading AI detection platform, we empower educators, students, journalists, marketers, and writers to navigate the evolving landscape of AI-generated content. With millions of users and institutions relying on us, we’re building a category-defining company at the intersection of AI and information integrity. Our team comes from high-performing engineering cultures, including Uber, Meta, Amazon, Affirm, and leading AI research labs, including Princeton, Caltech, MILA, and Vector.What we're looking forIn this role, you'll build the next-gen platform to verify the origin, quality, and factuality of the world's information. The ideal intern candidate is someone who is a voracious learner, has a history of building applications from the ground up, and can break down complex challenges.You'll be working on a fast-paced team of passionate builders and partnering closely with our ML and design teams, to create industry-defining software that has attracted over 2M users globally. Past intern projects have been the focus of demos to VCs and state-level policy leaders.ResponsibilitiesBuild and deploy high-impact, intuitive, AI-driven web apps in React, Node, and TailwindDevelop top-requested features from our users on our dashboard, chrome extensions, and APIUtilize product analytics to make data-driven product decisionsCollaborate with our ML, design, and business teams to develop new product initiativesWear multiple hats and work across the product stackQualificationsComfortable building end-to-end experiences from backend to CSS+2 years of experience with modern web frameworks (Express, Next.js, Typescript, and React)+1 years of experience with databases (PostgreSQL, AWS RDS)Highly motivated to make positive societal impactWork with 5 hours of overlap with Eastern Standard TimeBonus:strong open-source portfolioexperience working in an early-stage startup environmentexperience as a peer-edited writerWho you'll be joiningOur TeamYou will be working directly withAlex (our CTO) R&D at Uber self-driving division and Facebook, 3 patents in MLEdmond (our fullstack lead) Obama Foundation Scholar at Columbia University and Editor-in-chief of The Andela WayOlivia (our head of design) on translating your research into outputs for millions of users. Edward (our CEO, ex-Bellingcat, Microsoft, BBC investigative journalism) to craft the messages we send to our community, and shape the GPTZero brand.Additionally, you will be working with an experienced (eg. ex-Google, Meta, Microsoft, Bloomberg ML, Uber, Vector, MILA), diverse (eg. an engineering team with both Y-combinator and Obama scholarship recipients, a designer with art featured in the Met), and driven (eg. an operator who has scaled a company to 100M+ revenue and is committed to doing it again) group of individuals, described by one investor as one of the strongest founding teams seen in their career.Together, we are committed to making a permanent impact on the future of writing, and on humanity.Our Angels and Advisors Tom Glocer (Legendary Reuters CEO)Mark Thompson (Legendary NYT CEO and current CNN chief executive)Jack Altman (CEO of Lattice, brother of Sam Altman)Karthik Narasimhan (Princeton NLP Professor, co-author of OpenAI’s original GPT paper) Emad Mostaque (CEO of Stability AI)Doug Herrington (CEO of Worldwide Amazon Stores)Brad Smith (President of Microsoft)Tripp Jones (Partner at Uncork Capital)Ali Partovi (co-founder of Code.org, early investor in Dropbox and Airbnb)Russ Heddleston (CEO of Docsend)Alex Mashrabov (Snapchat, Director of AI)Faizan Mehdi (Affinity, Director of Demand Generation)Our Perks🏥 Health, dental, and mental health benefits💻 Hybrid work in Toronto and NYC offices🚀 Competitive salary🏝 Flexible PTO🎉 Regular company retreats💡Mentorship opportunities with our world-class team, advisors, and investors🙌 Wellness and learning stipend

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About the Program The Human Frontier Collective (HFC) brings together domain experts across research, clinical practice, and advanced professional work to contribute to high-impact projects in technology and reasoning systems. As a Medical Fellow, you will apply your clinical training to help develop and evaluate tools that interact with complex medical content. Your work will directly inform how emerging systems reason through diagnosis, triage, and patient care scenarios. PLEASE NOTE: This is a remote, contract-based role. We welcome international applicants based in the EU, Canada, Australia, and New Zealand. Engagements will run for approximately six months with flexible scheduling.  What You'll Do Design Complex Clinical Scenarios Create detailed case studies and clinical reasoning tasks across specialties to test how systems interpret symptoms, assess risks, and prioritize care. Evaluate Decision-Making Approaches Review and critique structured outputs for clinical safety, accuracy, and sound judgment. Identify errors in logic or inappropriate treatment suggestions. Shape Reasoning Frameworks Provide structured, example-driven feedback to improve how models understand differentials, guidelines, and clinical narratives. Work Across Specialized Projects Contribute to targeted workstreams in internal medicine, emergency care, radiology, psychiatry, and other domains aligned with your background. Who Should Apply Graduates of a licensed medical school (MD or DO), who are board certified and in residency / post residency / practicing / or with extensive practice Recent or current clinical experience in inpatient, outpatient, or academic settings Strong writing and clinical reasoning skills, with comfort assessing edge cases and nuanced scenarios Backgrounds welcome from internal medicine, emergency medicine, radiology, surgery, psychiatry, and related fields Nurse practitioners, physician assistants, and registered nurses with deep clinical experience may also be considered Fluency in written English is required Why Join the HFC? Contribute to High-Impact Work Apply your medical expertise to problems that require real judgment, not rote recall. Your input will directly influence how complex reasoning tasks are handled. Flexible Remote Work + Competitive Compensation Set your own schedule and contribute from anywhere. Most participants engage between 5-20 hours per week. Pathways for Growth High-impact contributors may be invited to join additional review projects, advisory roles, or research collaborations. How to Apply Submit your CV and a brief summary of your clinical background. Selected candidates will be invited to complete a short trial task and interview.PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI.  Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative AI Platform (SGP). The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an AAI Engineering Manager, you’ll manage a team of high-calibre Applied AI Engineers + MLEs who work with clients to train ML models to satisfy their business needs. Your team’s work will range from training next-generation AI cybersecurity firewall LLMs to training foundation agentic action models making predictions about business-saving outcomes. You will guide your  team towards using data-driven experiments to provide key insights around model strengths and inefficiencies in an effort to improve products. If you are excited about shaping the future of the modern AI movement, we would love to hear from you! You will:  Train state of the art models, developed both internally and from the community, in production to solve problems for our enterprise customers.  Manage a team of 5+ Applied AI Engineers / ML Engineers Work with product and research teams to identify opportunities for ongoing and upcoming services. Explore approaches that integrate human feedback and assisted evaluation into existing product lines.  Create state of the art techniques to integrate tool-calling into production-serving LLMs. Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems. Ideally you’d have: At least 3 years of model training, deployment and maintenance experience in a production environment At least 1-2 years of management or tech leadership experience Strong skills in NLP, LLMs and deep learning  Solid background in algorithms, data structures, and object-oriented programming Experience working with a cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment Experience building products with LLMs including knowing the ins and outs of evaluation, experimentation, and designing solutions to get the most of the models PhD or Masters in Computer Science or a related field Nice to haves: Experience in dealing with large scale AI problems, ideally in the generative-AI field Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. classification, detection, question-answering, etc.  Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc.  Strong written and verbal communication skills to operate in a cross functional team environment Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$212,000—$254,400 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI.  Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Lambda is the #1 GPU Cloud for ML/AI teams training, fine-tuning and inferencing AI models, where engineers can easily, securely and affordably build, test and deploy AI products at scale. Lambda’s product portfolio includes on-prem GPU systems, hosted GPUs across public & private clouds and managed inference services – servicing government, researchers, startups and Enterprises world-wide. If you'd like to build the world's best deep learning cloud, join us.  *Note: This position requires presence in our San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.In the world of distributed AI, raw GPU and CPU horsepower is just a part of the story. High-performance networking and storage are the critical components that enable and unite these systems, making groundbreaking AI training and inference possible.The Lambda Infrastructure Engineering organization forges the foundation of high-performance AI clusters by welding together the latest in AI storage, networking, GPU and CPU hardware.Our expertise lies at the intersection of:High-Performance Distributed Storage Solutions and Protocols: We engineer the protocols and systems that serve massive datasets at the speeds demanded by modern clustered GPUs.Dynamic Networking: We design advanced networks that provide multi-tenant security and intelligent routing without compromising performance, using the latest in AI networking hardware.Compute Virtualization: We enable cutting-edge virtualization and clustering that allows AI researchers and engineers to focus on AI workloads, not AI infrastructure, unleashing the full compute bandwidth of clustered GPUs.About the Role:We are seeking a seasoned Storage Engineering Manager with experience in the specification, evaluation, deployment, and management of HPC storage solutions across multiple datacenters to build out a world-class team. You will hire and guide a team of storage engineers in building storage infrastructure that serves our AI/ML infrastructure products, ensuring the seamless deployment and operational excellence of both the physical and logical storage infrastructure (including proprietary and open source solutions).Your role is not just to manage people, but to serve as the ultimate technical and operational authority for our high-performance, petabyte-scale storage solutions.Your leadership will be pivotal in ensuring our systems are not just high-performing, but also reliable, scalable, and manageable as we grow toward exascale.This is a unique opportunity to work at the intersection of large-scale distributed systems and the rapidly evolving field of artificial intelligence infrastructure. This is an opportunity to have a significant impact on the future of AI. You will be building the foundational infrastructure that powers some of the most advanced AI research and products in the world.What You’ll DoTeam Leadership & Management:Grow/Hire, lead, and mentor a top-talent team of high-performing storage engineers delivering HPC, petabyte-scale storage solutions.Foster a high-velocity culture of innovation, technical excellence, and collaboration.Conduct regular one-on-one meetings, provide constructive feedback, and support career development for team members.Drive outcomes by managing project priorities, deadlines, and deliverables using Agile methodologies.Technical Strategy & Execution:Drive the technical vision and strategy for Lambda distributed storage solutions.You will lead storage vendor selection criteria, vendor selection, and vendor relationship management (support, installation, scheduling, specification, procurement).Manage team in storage lifecycle management (installation, cabling, capacity upgrades, service, RMA, updating both hardware and software components as needed).You will guide choices around optimization of storage pools, sharding, and tiering/caching strategies.Lead team in tasks related to multi-tenant security, tenant provisioning, metering integration, storage protocol interconnection, and customer data-migration.Guide Storage SREs in development of scripting and automation tools for configuration management, monitoring, and operational tasks.Guide team in problem identification, requirements gathering, solution ideation, and stakeholder alignment on engineering RFCs.Lead the team in supporting customers.Cross-Functional Collaboration:Collaborate with the HPC Architecture team on drive selection, capacity determination, storage networking, cache placement, and rack layouts.Work closely with the storage software teams and networking teams to execute on cross-functional infrastructure initiatives and new data-center deployments including integration of storage protocols across a variety of on-prem storage solutions.Work with procurement data-center operations, and fleet engineering teams to deploy storage solutions into new and existing data centers.Work with vendors to troubleshoot customer performance, reliability, and data-integrity issues.Work closely with Networking, Compute, and Storage Software Engineering teams to deploy high-performance distributed storage solutions to serve AI/ML workloads.Partner with the fleet engineering team to ensure seamless deployment, monitoring, and maintenance of the distributed storage solutions.Innovation & Research:Stay current with the latest trends and research into AI and HPC storage technologies and vendor solutions.Guide team in investigating strategies for using Nvidia SuperNIC DPUs for storage edge-caching, offloading, and GPUDirect Storage capabilities.Work with the Lambda product team to uncover new trends in the AI inference and training product category that will inform emerging storage solutions.Encourage and support the team in exploring new technologies and approaches to improve system performance and efficiency.YouExperience:10+ years of experience in storage engineering with at least 5+ years in a management or lead role.Demonstrated experience leading a team of storage engineers and storage SREs on complex, cross-functional projects in a fast-paced startup environment.Extensive hands-on experience in designing, deploying, and maintaining distributed storage solutions in a CSP (Cloud Service Provider), NCP (Neo-Cloud provider), HPC-infrastructure integrator, or AI-infrastructure company.Experience with storage solutions serving storage volumes at a scale greater than 20PB.Strong project management skills, leading high-confidence planning, project execution, and delivery of team outcomes on schedule.Extensive experience with storage site reliability engineering.Experience with one or more of the following in an HPC or AI Infrastructure environment: Vast, DDN, Pure Storage, NetApp, Weka.Experience deploying CEPH at scale greater than 25PB.Technical Skills:Experience in serving one or more of the following storage protocols: object storage (e.g., S3), block storage (e.g., iSCSI), or file storage (e.g., NFS, SMB, Lustre).Professional individual contributor experience as a storage engineer or storage SRE.Familiarity with modern storage technologies (e.g., NVMe, RDMA, DPUs) and their role in optimizing performance.People Management:Experience building a high-performance team through deliberate hiring, upskilling, planned skills redundancy, performance-management, and expectation setting.Nice to HaveExperience:Experience driving cross-functional engineering management initiatives (coordinating events, strategic planning, coordinating large projects).Experience with NVidia SuperNIC DPUs for edge-caching (such as implementing GPUDirect Storage).Technical Skills:Deep experience with Vast, Weka and/or NetApp in an HPC or AI Infrastructure environment.Deep experience implementing CEPH in an HPC or AI infrastructure environment at a scale greater than 100PB.People Management:Experience driving organizational improvements (processes, systems, etc.)Experience training, or managing managers.Salary Range InformationThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About LambdaFounded in 2012, ~400 employees (2025) and growing fastWe offer generous cash & equity compensationOur investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitabilityOur research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOGHealth, dental, and vision coverage for you and your dependentsWellness and Commuter stipends for select roles401k Plan with 2% company match (USA employees)Flexible Paid Time Off Plan that we all actually useA Final Note:You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.Equal Opportunity EmployerLambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

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Lambda is the #1 GPU Cloud for ML/AI teams training, fine-tuning and inferencing AI models, where engineers can easily, securely and affordably build, test and deploy AI products at scale. Lambda’s product portfolio includes on-prem GPU systems, hosted GPUs across public & private clouds and managed inference services – servicing government, researchers, startups and Enterprises world-wide. If you'd like to build the world's best deep learning cloud, join us.  *Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.In the world of distributed AI, raw GPU and CPU horsepower is just a part of the story. High-performance networking and storage are the critical components that enable and unite these systems, making groundbreaking AI training and inference possible.The Lambda Infrastructure Engineering organization forges the foundation of high-performance AI clusters by welding together the latest in AI storage, networking, GPU and CPU hardware.Our expertise lies at the intersection of:High-Performance Distributed Storage Solutions and Protocols: We engineer the protocols and systems that serve massive datasets at the speeds demanded by modern clustered GPUs.Dynamic Networking: We design advanced networks that provide multi-tenant security and intelligent routing without compromising performance, using the latest in AI networking hardware.Compute Virtualization: We enable cutting-edge virtualization and clustering that allows AI researchers and engineers to focus on AI workloads, not AI infrastructure, unleashing the full compute bandwidth of clustered GPUs.About the Role:We are seeking an experienced Software Engineering Manager with a history in the development of storage protocols and distributed storage systems to lead a team of Storage Software Engineers and Distributed Systems Engineers in the design, development, and optimization of cutting-edge distributed storage solutions. Your team will be responsible for building high-performance, scalable, and reliable implementations of object, block, and file protocols, specifically tailored to serve performance demanding AI training and inference workloads. This is a unique opportunity to work at the intersection of large-scale distributed systems and the rapidly evolving field of artificial intelligence infrastructure. You will be building the foundational infrastructure that powers some of the most advanced AI research and products in the world.What You’ll DoTeam Leadership & Management:Grow/Hire, lead, and mentor a top-talent team of high-performing software engineers focused on delivering distributed storage protocols.Foster a high-velocity culture of innovation, technical excellence, and collaboration.Conduct regular one-on-one meetings, provide constructive feedback, and support career development for team members.Drive outcomes by managing project priorities, deadlines, and deliverables using Agile methodologies.Technical Strategy & Execution:Drive the technical vision and strategy for our distributed storage protocols (e.g., S3, NFS, iSCSI) and their underlying distributed systems.Oversee the development of highly optimized storage solutions designed to meet the performance demands of AI/ML workloads (e.g., high throughput, low latency, optimization for AI workload access patterns).Lead the team in tackling complex distributed systems challenges, including concurrency, consistency, fault tolerance, and data durability across multiple data centers.Guide engineering team in problem identification, requirements gathering, solution ideation, and stakeholder alignment on engineering RFCs.Deeply understand the performance bottlenecks of existing storage systems and guide the team in developing innovative solutions to overcome them.Lead the team in supporting customers.Cross-Functional Collaboration:Work closely with AI/ML research and products teams to understand customers storage needs and translate them into technical requirements.Work closely with the product engineering team to deliver high quality products to customers to meet their unique needs.Collaborate with product management to define the product roadmap and prioritize features.Work closely with HPC Architecture, Networking, Compute, and Storage Engineering teams to deploy high-performance distributed storage protocols to serve AI/ML workloads.Partner with fleet engineering and platforms teams to ensure seamless deployment, monitoring, and maintenance of the distributed storage protocols.Work in lock-step with the Storage Engineering team to provide reliable storage products on top of a variety of physical storage solutions.Innovation & Research:Stay current with the latest trends and research in distributed systems, storage technologies, and AI/ML hardware/software advancements.Work with the Lambda product team to uncover new trends in the AI inference and training product category.Encourage and support the team in exploring new technologies and approaches to improve system performance and efficiency.YouExperience:10+ years of experience in software development, with at least 5+ years in a management or lead role in storage software engineering.Demonstrated experience leading a team of software engineers on complex, cross-functional projects in a fast-paced startup environment.Extensive hands-on experience in designing and implementing distributed storage systems.Experience with storage protocols serving storage volumes at a scale greater than 20PB.Experience developing and tuning distributed storage protocols across scaling challenges using namespacing, sharding, and caching strategies.Familiarity with deploying and running applications on Kubernetes or other container orchestration systems (e.g., AWS ECS, Hashicorp Nomad).Strong project management skills, leading high-confidence planning, project execution, and delivery of team outcomes on schedule.Technical Skills:Knowledge in one or more of the following storage protocols: object storage (e.g., S3), block storage (e.g., iSCSI), or file storage (e.g., NFS, SMB, Lustre).Professional individual contributor experience in languages such as C++, Go, Rust, or Python.Familiarity with modern storage technologies (e.g., NVMe, RDMA) and their role in optimizing performance.Experience with containerization technologies (e.g., Docker, Kubernetes) and their integration with storage solutions.Distributed Systems Knowledge:Solid understanding of distributed systems concepts, including consensus algorithms (e.g., Raft, Paxos), distributed caching, failure recovery, consistency models (e.g., eventual consistency), fault tolerance, data replication, load balancing, and distributed consensus algorithmsPeople Management:Experience building a high-performance team through deliberate hiring, upskilling, planned skills redundancy, performance-management, and expectation setting.Nice to HaveExperience:Demonstrated delivery of distributed storage protocols in a CSP (Cloud Service Provider), NCP (Neo-Cloud provider), HPC-infrastructure integrator, or AI-infrastructure company.Experience with storage protocols serving storage volumes at a scale greater than 100PB.Implementation of distributed storage protocols backed by a variety of storage solutions, performance-tuned for AI/ML workloads.Experience driving cross-functional engineering management initiatives (coordinating deployments, strategic planning, coordinating large projects).Technical Skills:Deep expertise in one or more of the following storage protocols: object storage (e.g., S3), block storage (e.g., iSCSI), or file storage (e.g., NFS, SMB, Lustre).Strong programming skills in languages such as C++, Go, Rust, or Python.In-depth knowledge of operating system internals, including file systems, caching, and I/O scheduling.AI/ML Domain Knowledge:Experience working with AI/ML training and inference frameworks (e.g., TensorFlow, PyTorch).Understanding of the unique data access patterns and performance requirements of AI workloads.Distributed Systems Knowledge:Proven ability to design and debug highly concurrent and fault-tolerant systems.People Management:Experience driving organizational improvements (processes, systems, etc.)Experience training, or managing managers.Salary Range InformationThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About LambdaFounded in 2012, ~400 employees (2025) and growing fastWe offer generous cash & equity compensationOur investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitabilityOur research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOGHealth, dental, and vision coverage for you and your dependentsWellness and Commuter stipends for select roles401k Plan with 2% company match (USA employees)Flexible Paid Time Off Plan that we all actually useA Final Note:You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.Equal Opportunity EmployerLambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the team The Enterprise Agents Engineering Team at xAI is a team of builders solving the hardest problems in applied AI: integrating with messy systems, orchestrating complex workflows, and harnessing AI to transform business operations. We build full-stack solutions with ownership of end-to-end product execution from ideation to deployment, collaborating closely with our research team to incorporate cutting-edge AI advancements into robust and reliable user-centric solutions. Through an iterative development process, we work hand-in-hand with customers to gather feedback, refine features, and evolve products to address real-world challenges. About the role An ideal candidate meets at least the following requirements: Expert knowledge of either Rust or C++, Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems, Knowledge of service observability and reliability best practices, Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and CockroachDB Additionally, any of the below points will help a candidate stand out: Expert knowledge of Python, Experience with Docker, Kubernetes, and containerized applications, Expert knowledge of TypeScript, Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping), Hands-on experience with LLM APIs, embeddings, or RAG patterns Track record of delivering user-facing software at scale. Interview process After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15 minute interview (“phone interview”) during which a member of our team will ask some basic technical questions. If you clear the initial phone interview, you will enter the main process, which consists of at least two technical interviews: Coding interview in Rust or C++. Distributed systems design interview. Benefits Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. Annual Salary Range $180,000 - $440,000 USD  Benefits Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. xAI is an equal opportunity employer. California Consumer Privacy Act (CCPA) Notice

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Welcome to the video first world From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content. Today, people want to watch and listen, not read — both at home and at work. If you’re reading this and nodding, check out our brand video. Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale—until now…. Meet Synthesia We're on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organizations to communicate and share knowledge through video quickly and efficiently. We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2. In February 2024, G2 named us as the fastest growing company in the world. Today, we're at a $2.1bn valuation and we recently raised our Series D. This brings our total funding to over $330M from top-tier investors, including Accel, Nvidia, Kleiner Perkins, Google and top founders and operators including Stripe, Datadog, Miro, Webflow, and Facebook. What you'll do at Synthesia: You will work end-to-end, contributing to our client application written in React and our monolithic backend written in Python, and managing the safe release of your features to our customer base. You will have sole ownership of projects that span months, requiring you to have the ability to break a problem down into small steps that can be delivered and validated iteratively. You will work directly with the product manager responsible for your project, meaning that you will be expected to ideate and focus on the commercial problem that you're solving, and you will have the opportunity to shape the direction of the product. You will evaluate your own work, leveraging our data pipeline and frameworks that we have established to understand the impact your features have on our commercial objectives and pivoting where necessary. You will consider the long-term direction of the team, making sure that we are developing the engineering capabilities that will allow us to stay ahead of the challenges we are likely to encounter in 6-12 months' time.   What we're looking for: At least seven (7) years of experience as a software engineer, at least 3 on the senior/lead level. You have experience in a high-performing engineering team that is operating at scale. This could come from a scale-up environment or a more established organization recognised for building and shipping with a great engineering culture. An ability to work across the stack, with deep knowledge on client side, experience in implementing complex UI interactions is ideal. FE only experience is OK if you are happy to occasionally help out with BE. Relevant engineering experience for a team building an enterprise-grade SaaS product delivering AI-powered video generation; billing systems, experimentation platforms, video delivery systems, online editors, real-time collaboration and so on. Strong alignment with commercial success. Previous leadership experience of smaller teams is a plus.    Why join us? We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why, Our culture At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here. Serving 50,000+ customers (and 50% of the Fortune 500) We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2. Proprietary AI technology Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind. AI Safety, Ethics and Security AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always.  Learn more about our commitments to AI Ethics, Safety & Security.   The hiring process: 30-40min call with our technical recruiter 45min call with engineers about your past projects Take-home assignment (no alternative is offered) - does not have a deadline and is syntax-agnostic, so you're welcome to use the tools and languages you're most comfortable with. That said, we strongly prefer contributions using our core stack: React/TypeScript on the frontend, and Python/Flask on the backend. 60min technical discussion 30min call with leadership  The process does not need to take long - we can be done in seven working days.   Other important info: This is a remote role from an EU country, UK or Switzerland.  The salary starts at EUR/GBP/CHF 100.000 base + stock option plan. This is full-time employment only - no contractors possible - usually through OysterHR. Everyone at Synthesia gets 25 days of leave + local holidays (no extra paid or unpaid leave possible). We only sponsor VISA if you are in the UK/EU country already and need support - we do not relocate people.

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About Appier  Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the role [The seniority/title is determined by job-related skills, experience, and evaluation after the interview.]  We are looking for a data-driven and collaborative individual to join our team as an RTB Advertising Optimization PM. In this role, you will work closely with data scientists and campaign managers to improve RTB (Real-Time Bidding) campaign performance through model enhancements, strategic insights, and cross-team collaboration. You will have the opportunity to run large-scale A/B testing experiments on billions of ad requests daily, identify key signals that drive performance, and shape the optimization direction based on real-time data and industry trends. This is an ideal opportunity for someone who is passionate about advertising technology, machine learning applications, and performance marketing. Key Responsibilities: Partner with data scientists and campaign managers to improve RTB model and algorithm performance. Analyze competitor strategies and market trends to identify optimization opportunities. Drive data-informed decision-making to improve campaign outcomes. Design and evaluate A/B experiments at scale using billions of daily auction requests. Research and test end-to-end RTB ad serving behaviors to uncover areas for improvement. Explore and evaluate potential new signals to enhance model effectiveness. Collaborate with the SSP partnership team to optimize traffic quality and supply-side performance. Coordinate cross-functional requirements with strong communication and alignment across teams. Qualifications: Education: Background in Engineering, Data Science, Marketing, or related fields is a plus. Availability: Must be available full-time; based in TW preferred. Language Skills: Proficient in English and Mandarin; able to clearly articulate ideas and findings across technical and non-technical audiences. Bonus: Experience in digital advertising campaign operations, media buying, or performance optimization—especially within RTB environments—is a strong plus.   #LI-AK1

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🎤 Why voize? Because we’re more than just a job!At voize, we’re revolutionizing the healthcare industry with AI: Nurses simply speak their documentation into their smartphones, and our AI automatically generates the correct entries. This saves each nurse an average of 39 minutes per day, improves the quality of documentation, and makes their daily work much more rewarding.voize is YCombinator-funded, already in use at over 600 senior care homes, and has grown by 100% in the last 90 days. Our customers save over 3.5 million hours annually – time spent on people instead of paperwork.But this is just the beginning. With our self-developed voize AI, we’re transforming not only the healthcare industry, but also have the potential to create value in many other sectors – from healthcare to inspections.💡 Your Mission:If you're a Machine Learning Engineer experienced with Speech recognition and are excited to work at the cutting edge of product design, applied ML research, and MLOps, then go ahead and apply! With us, you'll build products with direct user feedback, train AI models with real data, and ship new features to production every day.🤝 Your Skillset – What you bring to the tableSeveral years hands-on experience in Deep Learning for speech recognition, including developing and optimising ASR-systems (not just academic research)Excellent foundation in STT (Speech-to-Text) system development with a focus on real-world applicationsExperience with owning the ML process end-to-end: from concept and exploration, to model productionization, maintenance, monitoring and optimizationShipped ML models to production with Python and PyTorchTrained new models from scratch and not just fine-tuning existing ones🚀 Your Daily Business – No two days are alikeTake ownership for the design, training, evaluation, and deployment of our deep learning models in the space of speech recognitionThe models you build and refine are at the heart of our applications and directly impact the end-userYou'll get to engineer large self-supervised trainings as well as fast inference for mobile devices and hosted environments🎯 Our Success Mindset – How we work at voizeResilience is one of your strengths – you see challenges as opportunities, not obstaclesIterative working suits you – you test, learn, and improve constantly instead of waiting for perfectionCommunication & feedback come naturally to you – you openly address issues and both give and receive constructive feedback🌱 Growing together – what you can expect at voizeBecome a co-creator of our success with virtual stock optionsOur office is in Berlin, and we offer remote workWe provide flexible working hours because you know best when you work most efficiently!Access to various learning platforms (e.g., Blinkist, Audible, etc.)We have an open culture and organize regular work weeks and team events to collaborate and bondWe are a fast-growing startup, so you'll encounter various challenges, providing the perfect foundation for rapid personal growthYour work will make a real impact, helping alleviate the workload for healthcare professionalsFree Germany Ticket and Urban Sports Club membership30 days of vacation – plus your birthday off✨ Ready to talk? Apply now! 🚀We look forward to your application and can’t wait to meet you – no matter who you are or what background you have!