Top Research Scientist Jobs Openings in 2025

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Applications will be reviewed on a rolling basis. We encourage candidates to apply early. The application window will close on October 31stAbout Handshake AIHandshake is building the career network for the AI economy. Our three-sided marketplace connects 18 million students and alumni, 1,500+ academic institutions across the U.S. and Europe, and 1 million employers to power how the next generation explores careers, builds skills, and gets hired.Handshake AI is a human data labeling business that leverages the scale of the largest early career network. We work directly with the world’s leading AI research labs to build a new generation of human data products. From PhDs in physics to undergrads fluent in LLMs, Handshake AI is the trusted partner for domain-specific data and evaluation at scale.This is a unique opportunity to join a fast-growing team shaping the future of AI through better data, better tools, and better systems—for experts, by experts.Now’s a great time to join Handshake. Here’s why:Leading the AI Career Revolution: Be part of the team redefining work in the AI economy for millions worldwide.Proven Market Demand: Deep employer partnerships across Fortune 500s and the world’s leading AI research labs.World-Class Team: Leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, just to name a few.Capitalized & Scaling: $3.5B valuation from top investors including Kleiner Perkins, True Ventures, Notable Capital, and more.About the RoleHandshake AI builds the data engines that power the next generation of large language models. Our research team works at the intersection of cutting-edge model post-training, rigorous evaluation, and data efficiency. Join us for a focused Summer 2026 internship where your work can ship directly into our production stack and become a publishable research contribution. To start between May and June 2026.Projects You Could TackleLLM Post-Training: Novel RLHF / GRPO pipelines, instruction-following refinements, reasoning-trace supervision.LLM Evaluation: New multilingual, long-horizon, or domain-specific benchmarks; automatic vs. human preference studies; robustness diagnostics.Data Efficiency: Active-learning loops, data value estimation, synthetic data generation, and low-resource fine-tuning strategies.Each intern owns a scoped research project, mentored by a senior scientist, with the explicit goal of an archive-ready manuscript or top-tier conference submission.Desired CapabilitiesCurrent PhD student in CS, ML, NLP, or related field.Publication track record at top venues (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.).Hands-on experience training and experimenting with LLMs (e.g., PyTorch, JAX, DeepSpeed, distributed training stacks).Strong empirical rigor and a passion for open-ended AI questions.Extra CreditPrior work on RLHF, evaluation tooling, or data selection methods.Contributions to open-source LLM frameworks.Public speaking or teaching experience (we often host internal reading groups).#LI-AG3

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Jasper is the leading AI marketing platform, enabling the world's most innovative companies to reimagine their end-to-end marketing workflows and drive higher ROI through increased brand consistency, efficiency, and personalization at scale. Jasper has been recognized as "one of the Top 15 Most Innovative AI Companies of 2024" by Fast Company and is trusted by nearly 20% of the Fortune 500 – including Prudential, Ulta Beauty, and Wayfair. Founded in 2021, Jasper is a remote-first organization with team members across the US, France, and Australia.About The RoleJasper Research is seeking a highly motivated intern to advance the frontiers of open source image-generation and image-editing applications. In this role, you will be instrumental in developing new state-of-the-art open-source text-to-image and image editing models while collaborating closely with our talented team of researchers and engineers. The internship duration is 6 months.We have historically relied on third-party existing open-source image foundational models for its core applications (replace-background, image uncropping, image relighting …), mastering model fine-tuning methods. One of the team’s current core projects consists now of building our own open-weights foundational text-to-image model from scratch.This role is open to candidates located in Paris. It will be a hybrid setup, which requires you to come into the office when necessary. What you will do at JasperAs a Research Scientist Intern, you will work closely with our research team to design and implement new methods to improve the sampling speed of diffusion models, such as, amongst others, re-flow, shortcut models or adversarial diffusion distillation. This role offers a unique opportunity to contribute to the development of a foundational open-source model, addressing challenges in scalability, fidelity, and generalization. You will engage in both theoretical and applied research, collaborating with experts in machine learning, computer vision, and natural language processing. The main goals of this internship are:Research & Development: Conduct literature reviews, propose and implement innovative methods to accelerate the sampling from diffusion models in the context of text-to-image and image editing.Model Training & Evaluation: Participate in the fine-tuning stages of the training of large-scale text-to-image models, conduct rigorous ablations, design evaluation metrics, and analyze model performance.Documentation & Communication: Document research findings, prepare technical reports, and participate in the external communication of the results.Open Source & Community: Contribute to an ambitious open-source project, publish research findings, and engage with the broader AI community.What you will bring to JasperCurrently enrolled in a Ph.D. or M.Sc program in Machine Learning, applied mathematics or computer science (Ph.D, preferred).Experience with distillation and/or improved sampling techniques for diffusion modelsA genuine interest in the field and a strong motivation to contribute to open-source initiatives, with a potentially proven track record through personal projects or previous experience in deep learning, especially generative models (e.g., diffusion models, GANs, VAEs, transformers).Strong coding abilities in Python and deep learning frameworks (PyTorch, TensorFlow, JAX).The ideal candidate will possess a strong critical thinking and problem-solving mindset, coupled with excellent teamwork skills.Being available for period of 6 months.Nice to haveStrong programming Python skills, including software engineering best practices to produce high-quality code.Experience with distributed training and large-scale systems on GPU clustersExperience with large-scale data processingContributions to open-source projects.Proven track record of achieving significant results as demonstrated by first-authored publications in major conferences and journals such as CVPR, ECCV, ICCV, ICLR, NeurIPSBenefits & PerksFlexible, hybrid work environment. Our office is based at Station F in Paris, the vibrant hub of the French startup ecosystem. Our efficient and lean team at Station F thrives on innovation and collaboration.Competitive compensation package

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Jasper is the leading AI marketing platform, enabling the world's most innovative companies to reimagine their end-to-end marketing workflows and drive higher ROI through increased brand consistency, efficiency, and personalization at scale. Jasper has been recognized as "one of the Top 15 Most Innovative AI Companies of 2024" by Fast Company and is trusted by nearly 20% of the Fortune 500 – including Prudential, Ulta Beauty, and Wayfair. Founded in 2021, Jasper is a remote-first organization with team members across the US, France, and Australia.About The RoleJasper Research is seeking a highly motivated intern to advance the frontiers of open source image-generation and image-editing applications. In this role, you will be instrumental in developing new state-of-the-art open-source text-to-image and image editing models while collaborating closely with our talented team of researchers and engineers. The internship duration is 6 months.We have historically relied on third-party existing open-source image foundational models for its core applications (replace-background, image uncropping, image relighting …), mastering model fine-tuning methods. One of the team’s current core projects consists now of building our own open-weights foundational text-to-image model from scratch.This role is open to candidates located in Paris. It will be a hybrid setup, which requires you to come into the office when necessary. What you will do at JasperAs a Research Scientist Intern, you will work closely with our research team to design the best-suited RLHF techniques for diffusion models. This role offers a unique opportunity to contribute to the development of a foundational open-source model, addressing challenges in scalability, fidelity, and generalization. You will engage in both theoretical and applied research, collaborating with experts in machine learning, computer vision, and natural language processing. The main goals of this internship areResearch & Development: Conduct literature reviews, propose and implement innovative methods to fine-tune text-to-image models with reinforcement learning methods (RLHF, DPO)Model Training & Evaluation: Participate in the fine-tuning stages of the training of large-scale text-to-image models, conduct rigorous ablations, design evaluation metrics, and analyze model performance.Documentation & Communication: Document research findings, prepare technical reports, and participate in the external communication of the results.Open Source & Community: Contribute to an ambitious open-source project, publish research findings, and engage with the broader AI community.What you will bring to JasperCurrently enrolled in a Ph.D. or M.Sc program in Machine Learning, applied mathematics or computer science (Ph.D, preferred).Experience with RLHF techniques with application to either Large Language Models or Diffusion Models.A genuine interest in the field and a strong motivation to contribute to open-source initiatives, with a potentially proven track record through personal projects or previous experience in deep learning, especially generative models (e.g., diffusion models, GANs, VAEs, transformers).Strong coding abilities in Python and deep learning frameworks (PyTorch, TensorFlow, JAX).The ideal candidate will possess a strong critical thinking and problem-solving mindset, coupled with excellent teamwork skills.Being available for period of 6 months.Nice to haveStrong programming Python skills, including software engineering best practices to produce high-quality code.Experience with distributed training and large-scale systems on GPU clustersExperience with large-scale data processingContributions to open-source projects.Proven track record of achieving significant results as demonstrated by first-authored publications in major conferences and journals such as CVPR, ECCV, ICCV, ICLR, NeurIPSBenefits & PerksFlexible, hybrid work environment. Our office is based at Station F in Paris, the vibrant hub of the French startup ecosystem. Our efficient and lean team at Station F thrives on innovation and collaboration.Competitive compensation package

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About Mistral At Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation, with teams distributed between Europe, the USA and Asia. We are creative, low-ego and team-spirited. At Mistral, we develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit. Mistral is hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI. What will you do *Research and develop novel methods to push the frontier of large language models*Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)*Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale*Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact About you * An expert in speech input/output methodologies (specific to audio)*You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)*You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)*You have high engineering competence. This means being able to design complex software and make it usable in production*You are a self-starter, autonomous and a team player Now, it would be ideal if* You have experience working with large-scale speech-language models*You have hands-on experience with training large transformer models in a distributed fashion*You can navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment *You have a strong publication record in a relevant scientific domain Note that this is not an exhaustive or necessary list of requirements. Please consider applying if you believe you have the skills to contribute to Mistral's mission. We value profile and experience diversity. Benefits France💰 Competitive cash salary and equity🥕 Food : Daily lunch vouchers🥎 Sport : Monthly contribution to a Gympass subscription 🚴 Transportation : Monthly contribution to a mobility pass🧑‍⚕️ Health : Full health insurance for you and your family🍼 Parental : Generous parental leave policy🌎 Visa sponsorship UK💰 Competitive cash salary and equity🚑 Insurance🚴 Transportation: Reimburse office parking charges, or 90GBP/month for public transport🥎 Sport: 90GBP/month reimbursement for gym membership🥕 Meal voucher: £200 monthly allowance for its meals💰 Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)

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Role OverviewWe are seeking a talented Research Scientist specializing in generative modeling and diffusion models to join our modeling team. This role is ideal for someone who is an expert at pre-training or post-training of large-scale diffusion models for images, videos, or 3D assets or scenes.You will collaborate closely with researchers, engineers, and product teams to bring advanced 3D modeling and machine learning techniques into real-world applications, ensuring that our technology remains at the forefront of visual innovation. This role involves significant hands-on research and engineering work, driving projects from conceptualization through to production deployment.Key ResponsibilitiesDesign, implement, and train large-scale diffusion models for generating 3D worldsDevelop and experiment with post-training for large-scale diffusion models to add novel control signals, adapt to target aesthetic preferences, or distill for efficient inferenceCollaborate closely with research and product teams to understand and translate product requirements into effective technical roadmaps.Contribute hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment.Continuously explore and integrate cutting-edge research in diffusion and generative AI more broadlyAct as a key technical resource within the team, mentoring colleagues, and driving best practices in generative modeling and ML engineeringIdeal Candidate Profile3+ years of experience in generative modeling or applied ML roles, ideally at a startup or other fast-paced research environmentExtensive experience with machine learning frameworks such as PyTorch or TensorFlow, especially in the context of diffusion models and other generative modelsDeep expertise in at least one area of generative modeling: pre-training, post-training, diffusion distillation, etc for diffusion modelsStrong history of publications or open-source contributions involving large-scale diffusion modelsStrong coding proficiency in Python and experience with GPU-accelerated computing.Ability to engage effectively with researchers and cross-functional teams, clearly translating complex technical ideas into actionable tasks and outcomes.Comfortable operating within a dynamic startup environment with high levels of ambiguity, ownership, and innovation.Nice to HaveContributions to open-source projects in the fields of computer vision, graphics, or ML.Familiarity with large-scale training infrastructure (e.g., multi-node GPU clusters, distributed training environments).Experience integrating machine learning models into production environments.Led or been involved with the development or training of large-scale, state-of-the-art generative models

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Role OverviewWe are seeking a talented Research Scientist specializing in 3D Models to join our modeling team. This role is ideal for someone passionate about developing and implementing cutting-edge 3D representation and machine learning models that generate sophisticated 3D scenes and objects, ranging from intricate details to expansive environments. You will collaborate closely with researchers, engineers, and product teams to bring advanced 3D modeling and machine learning techniques into real-world applications, ensuring that our technology remains at the forefront of visual innovation. This role involves significant hands-on research and engineering work, driving projects from conceptualization through to production deployment.Key ResponsibilitiesDevelop and implement state-of-the-art 3D representations and machine learning models to accurately capture and generate detailed 3D structures.Design and model small to large-scale objects and complex scenes, applying computer vision, graphics, and generative AI techniques.Collaborate closely with research and product teams to understand and translate product requirements into effective technical roadmaps.Contribute hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment.Continuously explore and integrate cutting-edge research in 3D modeling and generative AI.Act as a key technical resource within the team, mentoring colleagues, and driving best practices in 3D modeling and ML engineering.Ideal Candidate Profile3+ years of experience in 3D models, graphics, or applied ML roles, ideally within startup or fast-paced research environments.Extensive experience with machine learning frameworks such as PyTorch or TensorFlow, especially in the context of generative models and 3D representations.Deep expertise in at least one area of computer graphics, 3D reconstruction, neural rendering, generative AI for vision, or related fields.Proven ability to deliver high-quality 3D projects that involve complex object and scene generation.Strong academic track record or demonstrated expertise in 3D modeling, machine learning and/or rendering.Strong coding proficiency in Python and experience with GPU-accelerated computing.Ability to engage effectively with researchers and cross-functional teams, clearly translating complex technical ideas into actionable tasks and outcomes.Comfortable operating within a dynamic startup environment with high levels of ambiguity, ownership, and innovation.Nice to HaveContributions to open-source projects in the fields of computer vision, graphics, or ML.Familiarity with large-scale training infrastructure (e.g., multi-node GPU clusters, distributed training environments).Experience integrating machine learning models into production environments.Experience writing custom graphics or rendering related CUDA operators for use in ML frameworks such as PyTorch

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About us:At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business.Job Description:Articul8 AI is seeking an exceptional Principal AI Researcher to join us in shaping the future of Generative Artificial Intelligence (GenAI). As a member of our Applied Research team, you will be responsible for conducting cutting-edge research to advance the capabilities of our AI systems. Your role will involve designing, implementing, and evaluating novel approaches to improve our GenAI models, working at the intersection of GenAI research and product development.Responsibilities:Serve as the subject matter expert in various domains of GenAI research and development, including:Data pipelines: Design and optimize data processing workflows for large-scale model trainingTraining methodologies: Implement pre-training, mid-training, and post-training strategies and optimization techniquesReinforcement learning: Develop RL algorithms for GenAI and with applications in decision-making, personalization, and several other tasksMultimodal AI: Create systems that effectively process and generate across text, image, audio, and video modalitiesPersonalization: Design and implement tailored GenAI experiences by understanding user behavior, preferences, and contexts to deliver customized content and recommendationsKnowledge representation and retrieval: Develop techniques for effectively representation of information and knowledge elicitation, as well as search and retrieval.Play a technical leadership role in designing, developing, and scaling novel algorithms and models by taking them from research prototypes to production-ready systems that deliver real-world impactLead groundbreaking research initiatives in GenAI by identifying high-impact problems, designing innovative experiments, and developing solutions that advance both theoretical understanding and practical applications.Drive strategic decision-making processes by contributing to technology assessment, roadmap planning, and identifying areas for innovation that align with Articul8's business objectives.Partner with cross-functional teams to integrate cutting-edge research findings into products and maintain our technological leadership in the market.Monitor and analyze emerging trends in generative AI and related fields, sharing valuable research contributions through publications at prestigious conferences and journals.Mentor and guide junior team members and help building a strong culture of rapid innovation.Required Qualifications:Education: PhD/MSc degree in Computer Science, Machine Learning (ML), or a related field.Professional experience: 8+ years of experience as an AI researcher with a track record of applied research and/or product development (out of which, at least 3+ years should be on actively developing GenAI technologies).Core technical skills:Experience developing tools, libraries, and infrastructure for data preprocessing, model training/finetuning, and deployment of LLMs in research and production environments.A strong background in parallel/distributed computing on the cloud.Machine learning, deep learning, probability theory and statistics, natural language processing, computer vision, data wrangling and preparation, model evaluation and interpretation.Programming Skills: Proficiency in programming languages such as Python and experience working with version control systems (e.g., Git) and collaborating on code repositories is crucial.Preferred Qualifications:Experience with cloud computing platforms such as AWS, Azure, or GCP.Proven track record of publications in top-tier conferences and journals.Professional Attributes:Problem Solving: ability to break down complex problems into manageable components, devising creative solutions, and iteratively refining ideas based on feedback and experimental evidence.Collaboration and Communication: proficiency in working within cross-functional teams - communicating clearly, providing constructive criticism, delegating responsibilities, and respecting diverse perspectives.Critical Thinking: ability to carefully evaluate assumptions, questioning established methodologies, challenging own biases, and maintaining skepticism when interpreting results.Curiosity and Continuous Learning: ability to stay curious about advances in related fields and constantly seeking opportunities to expand knowledge base.Emotional Intelligence and Intellectual Humility: capable of displaying empathy, resilience, adaptability, and self-awareness. Ability to recognize own limitations, embracing uncertainty, acknowledging mistakes, and valuing others' contributions.If you're ready to join a team that's changing the game, apply now to become a part of the Articul8 team.

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About us:At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business.Job Description:Articul8 AI is seeking an exceptional Senior/Staff AI Researcher to join us in shaping the future of Generative Artificial Intelligence (GenAI). As a member of our Applied Research team, you will be responsible for conducting cutting-edge research to advance the capabilities of our AI systems. Your role will involve designing, implementing, and evaluating novel approaches to improve our GenAI models, working at the intersection of GenAI research and product development.Responsibilities:Serve as the subject matter expert in various domains of GenAI research and development, including:Data pipelines: Design and optimize data processing workflows for large-scale model trainingTraining methodologies: Implement pre-training, mid-training, and post-training strategies and optimization techniquesReinforcement learning: Develop RL algorithms for GenAI and with applications in decision-making, personalization, and several other tasksMultimodal AI: Create systems that effectively process and generate across text, image, audio, and video modalitiesPersonalization: Design and implement tailored GenAI experiences by understanding user behavior, preferences, and contexts to deliver customized content and recommendationsKnowledge representation and retrieval: Develop techniques for effectively representation of information and knowledge elicitation, as well as search and retrieval.Play a technical leadership role in designing, developing, and scaling novel algorithms and models by taking them from research prototypes to production-ready systems that deliver real-world impact.Partner with cross-functional teams to integrate cutting-edge research findings into products and maintain our technological leadership in the market.Monitor and analyze emerging trends in generative AI and related fields, sharing valuable research contributions through publications at prestigious conferences and journals.Required Qualifications:Education: PhD/MSc degree in Computer Science, Machine Learning (ML), or a related field.Professional experience: 5+ years of experience as an AI researcher with a track record of applied research and/or product development (out of which, at least 2+ years should be on actively developing GenAI technologies).Core technical skills:Experience developing tools, libraries, and infrastructure for data preprocessing, model training/finetuning, and deployment of LLMs in research and production environments.A strong background in parallel/distributed computing on the cloud.Machine learning, deep learning, probability theory and statistics, natural language processing, computer vision, data wrangling and preparation, model evaluation and interpretation.Programming Skills: Proficiency in programming languages such as Python and experience working with version control systems (e.g., Git) and collaborating on code repositories is crucial.Preferred Qualifications:Experience with cloud computing platforms such as AWS, Azure, or GCP.Proven track record of publications in top-tier conferences and journals.Professional Attributes:Problem Solving: ability to break down complex problems into manageable components, devising creative solutions, and iteratively refining ideas based on feedback and experimental evidence.Collaboration and Communication: proficiency in working within cross-functional teams - communicating clearly, providing constructive criticism, delegating responsibilities, and respecting diverse perspectives.Critical Thinking: ability to carefully evaluate assumptions, questioning established methodologies, challenging own biases, and maintaining skepticism when interpreting results.Curiosity and Continuous Learning: ability to stay curious about advances in related fields and constantly seeking opportunities to expand knowledge base.Emotional Intelligence and Intellectual Humility: capable of displaying empathy, resilience, adaptability, and self-awareness. Ability to recognize own limitations, embracing uncertainty, acknowledging mistakes, and valuing others' contributions.If you're ready to join a team that's changing the game, apply now to become a part of the Articul8 team. NOTE: This position is available via CLT contract only, Thank you!

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Who We Are At PathAI, we’re building an AI-powered platform for pathology to advance the diagnosis and treatment of disease and to improve the lives of patients. We’re applying our work to drug development, clinical diagnosis, and global health. What You’ll Do The day-to-day responsibilities for the Director of Translational Research, Oncology at PathAI include: Oversee execution of multiple translational research projects/contracts with key clients to meet company goals and strengthen partner relationships Oversee execution of multiple programs to drive company-wide scientific and business strategy Develop client relationships and pursue new opportunities to drive business growth Responsible for professional development of team of program / project managers / support staff Responsible for hiring and training activities Collaborate and liaise across internal stakeholders including the business development, product, and machine learning teams, providing hypotheses for novel biological insights and strategy roadmaps for project completion. What You Bring Advanced degree in life sciences or biomedical engineering-related disciplines required, PhD preferred. At least 5 years work experience Experience building, leading and managing teams. Strong user of technology with a solid basis in quantitative analysis and data-driven decision making Intellectual curiosity and the ability to learn quickly in a complex space Excellent communication skills Publications of research in related fields  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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About the TeamThe Personality & Model Behavior team conducts research on how to shape personalities and guide the behavior of models. We think about topics such as emotional intelligence, reasoning, and how models interact thoughtfully with users. We integrate those research into the final products of OpenAI that are used by hundreds of millions of users.  About the RoleWe’re looking for people who are experts in the fields such as reinforcement learning, machine learning, natural language processing, etc. Join us if you are passionate about tackling cutting-edge, open-ended research challenges and transforming your findings into real-world products.In this role, you will:Conduct research around personality and model behavior, leveraging and developing tools such as synthetic data, reinforcement learning, reasoning to shape the personality and model behavior, including models such as o3, o4-mini, 4o, etc.Build evaluations and pipelines to facilitate the development and research.Innovate new post-training methods.Integrate your research into the final product of OpenAI. You might thrive in this role if you:Have a deep understanding of machine learning and its applications.Have prior knowledge in training and optimizing models and building evaluations.Are willing to dive into large ML codebases to debug issues.Thrive in dynamic and technically complex environments.Have a track record of delivering innovative, out-of-the-box solutions to address real-world constraints.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.Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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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Scale is the leading data and evaluation partner for frontier AI companies, playing an integral role in advancing the science of evaluating and characterizing large language models (LLMs). Our research focuses on tackling the hardest problems in scalable oversight and the evaluation of advanced AI capabilities. We collaborate broadly across industry and academia and regularly publish our findings.  Our Research team is shaping the next generation of evaluation science for frontier AI models and works at the leading edge of model assessment and oversight. Some of our current research includes: Developing AI-assisted evaluation pipelines, where models help critique, grade, and explain outputs (e.g. RLAIF, model-judging-model). Advancing scalable oversight methods, such as rubric-guided evaluations, recursive oversight, and weak-to-strong generalization.  Designing benchmarks for frontier capabilities (e.g. reasoning, coding, multi-modal, and agentic tasks), inspired by efforts like MMMU, GPQA, SWE-Bench. Building evaluation frameworks for agentic systems, measuring multi-step workflows and real-world task success. You will: Lead a team of research scientists and engineers on foundational work in evaluation and oversight. Drive research initiatives on frameworks and benchmarks for frontier AI models, spanning reasoning, coding, multi-modal, and agentic behaviors. Design and advance scalable oversight methods, leveraging model-assisted evaluation, rubric-guided judgments, and recursive oversight. Collaborate with leading research labs across industry and academia. Publish research at top-tier venues and contribute to open-source benchmarking initiatives. Remain deeply engaged with the research community, both understanding trends and setting them. Ideally you'd have: Track record of impactful research in machine learning, especially in generative AI, evaluation, or oversight. Significant experience leading ML research in academia or industry. Strong written and verbal communication skills for cross-functional collaboration. Experience building and mentoring teams of research scientists and engineers. Publications at major ML/AI conferences (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR) and/or journals.   Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We do not ask LeetCode-style questions.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:$260,000—$350,000 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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About us:At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business.Job Description:Articul8 AI is seeking an exceptional Senior/Staff AI Researcher to join us in shaping the future of Generative Artificial Intelligence (GenAI). As a member of our Applied Research team, you will be responsible for conducting cutting-edge research to advance the capabilities of our AI systems. Your role will involve designing, implementing, and evaluating novel approaches to improve our GenAI models, working at the intersection of GenAI research and product development.Responsibilities:Serve as the subject matter expert in various domains of GenAI research and development, including:Data pipelines: Design and optimize data processing workflows for large-scale model trainingTraining methodologies: Implement pre-training, mid-training, and post-training strategies and optimization techniquesReinforcement learning: Develop RL algorithms for GenAI and with applications in decision-making, personalization, and several other tasksMultimodal AI: Create systems that effectively process and generate across text, image, audio, and video modalitiesPersonalization: Design and implement tailored GenAI experiences by understanding user behavior, preferences, and contexts to deliver customized content and recommendationsKnowledge representation and retrieval: Develop techniques for effectively representation of information and knowledge elicitation, as well as search and retrieval.Play a technical leadership role in designing, developing, and scaling novel algorithms and models by taking them from research prototypes to production-ready systems that deliver real-world impact.Partner with cross-functional teams to integrate cutting-edge research findings into products and maintain our technological leadership in the market.Monitor and analyze emerging trends in generative AI and related fields, sharing valuable research contributions through publications at prestigious conferences and journals.Required Qualifications:Education: PhD/MSc degree in Computer Science, Machine Learning (ML), or a related field.Professional experience: 5+ years of experience as an AI researcher with a track record of applied research and/or product development (out of which, at least 2+ years should be on actively developing GenAI technologies).Core technical skills:Experience developing tools, libraries, and infrastructure for data preprocessing, model training/finetuning, and deployment of LLMs in research and production environments.A strong background in parallel/distributed computing on the cloud.Machine learning, deep learning, probability theory and statistics, natural language processing, computer vision, data wrangling and preparation, model evaluation and interpretation.Programming Skills: Proficiency in programming languages such as Python and experience working with version control systems (e.g., Git) and collaborating on code repositories is crucial.Preferred Qualifications:Experience with cloud computing platforms such as AWS, Azure, or GCP.Proven track record of publications in top-tier conferences and journals.Professional Attributes:Problem Solving: ability to break down complex problems into manageable components, devising creative solutions, and iteratively refining ideas based on feedback and experimental evidence.Collaboration and Communication: proficiency in working within cross-functional teams - communicating clearly, providing constructive criticism, delegating responsibilities, and respecting diverse perspectives.Critical Thinking: ability to carefully evaluate assumptions, questioning established methodologies, challenging own biases, and maintaining skepticism when interpreting results.Curiosity and Continuous Learning: ability to stay curious about advances in related fields and constantly seeking opportunities to expand knowledge base.Emotional Intelligence and Intellectual Humility: capable of displaying empathy, resilience, adaptability, and self-awareness. Ability to recognize own limitations, embracing uncertainty, acknowledging mistakes, and valuing others' contributions.If you're ready to join a team that's changing the game, apply now to become a part of the Articul8 team.

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AI Researcher Job DescriptionAt AGI Inc., we're not just redefining AI-human interaction—we're creating a world where humans and AI amplify each other's potential. Leveraging breakthrough agentic reasoning capabilities, we aim to bring genuinely useful AGI into everyday life. Backed by years of research, AGI Inc. is pioneering the large-scale deployment of intelligent Consumer AI Agents that simplify, streamline, and elevate everyday experiences.Our team comprises elite ex-entrepreneurs, AI researchers, and product experts from Stanford, Berkeley, Nvidia, and DeepMind, supported by top investors in Silicon Valley. Our founder, Div Garg, is a Stanford AI PhD dropout and previously founded MultiOn, a leading AI Agent startup that introduced browser agents to the world, supported by General Catalyst, Forerunner, Samsung, and Amazon.At AGI Inc., we believe in fusing human insight with cutting-edge AI to craft experiences that are as intuitive as they are groundbreaking, paving the way toward everyday AGI. Our agentic products feel like a natural extension of who you are—an ever-present partner for ideas, projects, and solutions.About the RoleAs an AI Researcher at AGI Inc., you'll be at the forefront of developing novel algorithms and techniques for our browser-based intelligent agents. You'll bridge the gap between theoretical AI research and practical product applications, working on challenges that push the boundaries of what browser agents can accomplish. Your research will directly influence our product roadmap and contribute to the scientific community through publications and open-source contributions. This role offers a unique opportunity to work in an environment that values both academic rigor and real-world impact.Key ResponsibilitiesPioneer Novel Research: Lead research initiatives in areas such as reinforcement learning, multi-agent systems, and natural language understanding to enhance our browser agents' capabilities.Translate Research to Products: Work closely with engineering and product teams to implement research findings into products that deliver tangible value to users.Contribute to the Scientific Community: Publish high-quality research papers at top AI conferences (NeurIPS, ICML, ICLR, ACL) and participate in the open-source AI ecosystem.Develop Technical Roadmaps: Help define our technical research strategy, identifying promising areas that align with our product vision.Mentor and Collaborate: Work with and mentor other researchers and engineers, fostering a culture of scientific excellence and innovation.QualificationsEducation: MS or PhD in Computer Science, Machine Learning, AI, or a related technical field from a top university. Exceptional candidates with bachelor's degrees and equivalent research experience will also be considered.Research Experience: Demonstrated research experience in machine learning, NLP, reinforcement learning, or multimodal systems, evidenced by publications, open-source contributions, or impactful projects.Technical Skills: Strong programming skills in Python and experience with deep learning frameworks (PyTorch, TensorFlow). Familiarity with large language models, web technologies, and browser automation is a plus.Problem-Solving: Exceptional analytical thinking and creativity in approaching complex AI problems with novel solutions.Communication: Ability to explain complex technical concepts clearly and collaborate effectively with cross-functional teams.Startup Mindset: Enthusiasm for fast-paced environments, comfort with ambiguity, and a desire to build products that millions of people will use.Why Join Us?Dual Impact: Contribute to cutting-edge AI research while seeing your work directly impact products used by real people.Resources: Access to substantial compute resources, large datasets, and the latest AI technologies to support your research.Autonomy: Freedom to pursue research directions aligned with our mission, with less bureaucracy than traditional research labs.Equity: Competitive compensation package with significant equity, aligning your success with the company's growth.Community: Work alongside world-class researchers, engineers, and designers who are passionate about advancing the field of AI.How to ApplyWe'd love to see what you've built. Please include your resume, links to your publications or GitHub repositories, and a brief research statement outlining your interests and how they align with our mission.We can't wait to see your contributions to AI—and to welcome you to the AGI Inc. team!

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Company OverviewDeepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than DeepgramThe OpportunityVoice is the most natural modality for human interaction with machines. However, current sequence modeling paradigms based on jointly scaling model and data cannot deliver voice AI capable of universal human interaction. The challenges are rooted in fundamental data problems posed by audio: real-world audio data is scarce and enormously diverse, spanning a vast space of voices, speaking styles, and acoustic conditions. Even if billions of hours of audio were accessible, its inherent high dimensionality creates computational and storage costs that make training and deployment prohibitively expensive at world scale. We believe that entirely new paradigms for audio AI are needed to overcome these challenges and make voice interaction accessible to everyone. The RoleAs a Member of the Research Staff, you will pioneer the development of Latent Space Models (LSMs), a new approach that aims to solve the fundamental data, scale, and cost challenges associated with building robust, contextualized voice AI. Your research will focus on solving one or more of the following problems:Build next-generation neural audio codecs that achieve extreme, low bit-rate compression and high fidelity reconstruction across a world-scale corpus of general audio.Pioneer steerable generative models that can synthesize the full diversity of human speech from the codec latent representation, from casual conversation to highly emotional expression to complex multi-speaker scenarios with environmental noise and overlapping speech.Develop embedding systems that cleanly factorize the codec latent space into interpretable dimensions of speaker, content, style, environment, and channel effects -- enabling precise control over each aspect and the ability to massively amplify an existing seed dataset through “latent recombination”.Leverage latent recombination to generate synthetic audio data at previously impossible scales, unlocking joint model and data scaling paradigms for audio.  Endeavor to train multimodal speech-to-speech systems that can 1) understand any human irrespective of their demographics, state, or environment and 2) produce empathic, human-like responses that achieve conversational or task-oriented objectives.   Design model architectures, training schemes, and inference algorithms that are adapted for hardware at the bare metal enabling cost efficient training on billion-hour datasets and powering real-time inference for hundreds of millions of concurrent conversations.The ChallengeWe are seeking researchers who:See "unsolved" problems as opportunities to pioneer entirely new approachesCan identify the one critical experiment that will validate or kill an idea in days, not monthsHave the vision to scale successful proofs-of-concept 100xAre obsessed with using AI to automate and amplify your own impactIf you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative. It's Important to Us That You HaveStrong mathematical foundation in statistical learning theory, particularly in areas relevant to self-supervised and multimodal learningDeep expertise in foundation model architectures, with an understanding of how to scale training across multiple modalitiesProven ability to bridge theory and practice—someone who can both derive novel mathematical formulations and implement them efficientlyDemonstrated ability to build data pipelines that can process and curate massive datasets while maintaining quality and diversityTrack record of designing controlled experiments that isolate the impact of architectural innovations and validate theoretical insightsExperience optimizing models for real-world deployment, including knowledge of hardware constraints and efficiency techniquesHistory of open-source contributions or research publications that have advanced the state of the art in speech/language AI How We Generated This Job DescriptionThis job description was generated in two parts.  The “Opportunity”, “Role”, and “Challenge” sections were generated by a human using Claude-3.5-sonnet as a writing partner.  The objective of these sections is to clearly state the problem that Deepgram is attempting to solve, how we intend to solve it, and some guidelines to help you decide if Deepgram is right for you. Therefore, it is important that this section was articulated by a human.  The “It’s Important to Us” section was automatically derived from a multi-stage LLM analysis (using o1) of key foundational deep learning papers related to our research goals.  This work was completed as an experiment to test the hypothesis that traits of highly productive and impactful researchers are reflected directly in their work. The analysis focused on understanding how successful researchers approach problems, from mathematical foundations through to practical deployment. The problems Deepgram aims to solve are immensely difficult and span multiple disciplines and specialties. As such, we chose seminal papers that we believe reflect the pioneering work and exemplary human characteristics needed for success. The LLM analysis culminates in an “Ideal Researcher Profile”, which is reproduced below along with the list of foundational papers.  Ideal Researcher ProfileAn ideal researcher, as evidenced by the recurring themes across these foundational papers, excels in five key areas: (1) Statistical & Mathematical Foundations, (2) Algorithmic Innovation & Implementation, (3) Data-Driven & Scalable Systems, (4) Hardware & Systems Understanding, and (5) Rigorous Experimental Design. Below is a synthesis of how each paper highlights these qualities, with references illustrating why they matter for building robust, impactful deep learning models. 1. Statistical & Mathematical FoundationsMastery of Core ConceptsMany papers, like Scaling Laws for Neural Language Models and Neural Discrete Representation Learning (VQ-VAE), reflect the importance of power-law analyses, derivation of novel losses, or adaptation of fundamental equations (e.g., in VQ-VAE's commitment loss or rectified flows in Scaling Rectified Flow Transformers). Such mathematical grounding clarifies why models converge or suffer collapse.Combining Existing Theories in Novel WaysPapers such as Moshi (combining text modeling, audio codecs, and hierarchical generative modeling) and Finite Scalar Quantization (FSQ's adaptation of classic scalar quantization to replace vector-quantized representations) show how reusing but reimagining known techniques can yield breakthroughs. Many references (e.g., the structured state-space duality in Transformers are SSMs) underscore how unifying previously separate research lines can reveal powerful algorithmic or theoretical insights.Logical Reasoning and Assumption TestingAcross all papers—particularly in the problem statements of Whisper or Rectified Flow Transformers—the authors present assumptions (e.g., "scaling data leads to zero-shot robustness" or "straight-line noise injection improves sample efficiency") and systematically verify them with thorough empirical results. An ideal researcher similarly grounds new ideas in well-formed, testable hypotheses. 2. Algorithmic Innovation & ImplementationCreative Solutions to Known BottlenecksEach paper puts forth a unique algorithmic contribution—Rectified Flow Transformers redefines standard diffusion paths, FSQ proposes simpler scalar quantizations contrasted with VQ, phi-3 mini relies on curated data and blocksparse attention, and Mamba-2 merges SSM speed with attention concepts.Turning Theory into PracticeWhether it's the direct preference optimization (DPO) for alignment in phi-3 or the residual vector quantization in SoundStream, these works show that bridging design insights with implementable prototypes is essential.Clear Impact Through Prototypes & Open-SourceMany references (Whisper, neural discrete representation learning, Mamba-2) highlight releasing code or pretrained models, enabling the broader community to replicate and build upon new methods. This premise of collaboration fosters faster progress. 3. Data-Driven & Scalable SystemsEmphasis on Large-Scale Data and Efficient PipelinesPapers such as Robust Speech Recognition via Large-Scale Weak Supervision (Whisper) and BASE TTS demonstrate that collecting and processing hundreds of thousands of hours of real-world audio can unlock new capabilities in zero-shot or low-resource domains. Meanwhile, phi-3 Technical Report shows that filtering and curating data at scale (e.g., "data optimal regime") can yield high performance even in smaller models.Strategic Use of Data for Staged TrainingA recurring strategy is to vary sources of data or the order of tasks. Whisper trains on multilingual tasks, BASE TTS uses subsets/stages for pretraining on speech tokens, and phi-3 deploys multiple training phases (web data, then synthetic data). This systematic approach to data underscores how an ideal researcher designs training curricula and data filtering protocols for maximum performance. 4. Hardware & Systems UnderstandingEfficient Implementations at ScaleMany works illustrate how researchers tune architectures for modern accelerators: the In-Datacenter TPU paper exemplifies domain-specific hardware design for dense matrix multiplications, while phi-3 leverages blocksparse attention and custom Triton kernels to run advanced LLMs on resource-limited devices.Real-Time & On-Device ConstraintsSoundStream shows how to compress audio in real time on a smartphone CPU, demonstrating that knowledge of hardware constraints (latency, limited memory) drives design choices. Similarly, Moshi's low-latency streaming TTS and phi-3-mini's phone-based inference highlight that an ideal researcher must adapt algorithms to resource limits while maintaining robustness.Architectural & Optimization DetailsPapers like Mamba-2 in Transformers are SSMs and the In-Datacenter TPU work show how exploiting specialized matrix decomposition, custom memory hierarchies, or quantization approaches can lead to breakthroughs in speed or energy efficiency. 5. Rigorous Experimental DesignControlled Comparisons & AblationsNearly all papers—Whisper, FSQ, Mamba-2, BASE TTS—use systematic ablations to isolate the impact of individual components (e.g., ablation on vector-quantization vs. scalar quantization in FSQ, or size of codebooks in VQ-VAEs). This approach reveals which design decisions truly matter.Multifold Evaluation MetricsFrom MUSHRA listening tests (SoundStream, BASE TTS) to FID in image synthesis (Scaling Rectified Flow Transformers, FSQ) to perplexity or zero-shot generalization in language (phi-3, Scaling Laws for Neural Language Models), the works demonstrate the value of comprehensive, carefully chosen metrics.Stress Tests & Edge CasesWhisper's out-of-distribution speech benchmarks, SoundStream's evaluation on speech + music, or Mamba-2's performance on multi-query associative recall demonstrate the importance of specialized challenge sets. Researchers who craft or adopt rigorous benchmarks and "red-team" their models (as in phi-3 safety alignment) are better prepared to address real-world complexities. SummaryOverall, an ideal researcher in deep learning consistently demonstrates:A solid grounding in theoretical and statistical principlesA talent for proposing and validating new algorithmic solutionsThe capacity to orchestrate data pipelines that scale and reflect real-world diversityAwareness of hardware constraints and system-level trade-offs for efficiencyThorough and transparent experimental practicesThese qualities surface across research on speech (Whisper, BASE TTS), language modeling (Scaling Laws, phi-3), specialized hardware (TPU, Transformers are SSMs), and new representation methods (VQ-VAE, FSQ, SoundStream). By balancing these attributes—rigorous math, innovative algorithms, large-scale data engineering, hardware-savvy optimizations, and reproducible experimentation—researchers can produce impactful, trustworthy advancements in foundational deep learning. Foundational PapersThis job description was generated through analysis of the following papers:Robust Speech Recognition via Large-Scale Weak Supervision (arXiv:2212.04356)Moshi: a speech-text foundation model for real-time dialogue (arXiv:2410.00037)Scaling Rectified Flow Transformers for High-Resolution Image Synthesis (arXiv:2403.03206)Scaling Laws for Neural Language Models (arXiv:2001.08361)BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data (arXiv:2402.08093)In-Datacenter Performance Analysis of a Tensor Processing Unit (arXiv:1704.04760)Neural Discrete Representation Learning (arXiv:1711.00937)SoundStream: An End-to-End Neural Audio Codec (arXiv:2107.03312)Finite Scalar Quantization: VQ-VAE Made Simple (arXiv:2309.15505)Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone (arXiv:2404.14219)Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality (arXiv:2405.21060)Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $85 million in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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Company OverviewDeepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than DeepgramThe OpportunityVoice is the most natural modality for human interaction with machines. However, current sequence modeling paradigms based on jointly scaling model and data cannot deliver voice AI capable of universal human interaction. The challenges are rooted in fundamental data problems posed by audio: real-world audio data is scarce and enormously diverse, spanning a vast space of voices, speaking styles, and acoustic conditions. Even if billions of hours of audio were accessible, its inherent high dimensionality creates computational and storage costs that make training and deployment prohibitively expensive at world scale. We believe that entirely new paradigms for audio AI are needed to overcome these challenges and make voice interaction accessible to everyone. The RoleDeepgram is currently looking for an experienced researcher to who has worked extensively with Large Language Models (LLMS) and has a deep understanding of transformer architecture to join our Research Staff. As a Member of the Research Staff, this individual should have extensive experience working on the hard technical aspects of LLMs, such as data curation, distributed large-scale training, optimization of transformer architecture, and Reinforcement Learning (RL) training.The ChallengeWe are seeking researchers who:See "unsolved" problems as opportunities to pioneer entirely new approachesCan identify the one critical experiment that will validate or kill an idea in days, not monthsHave the vision to scale successful proofs-of-concept 100xAre obsessed with using AI to automate and amplify your own impactIf you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative.What You'll DoBrainstorming and collaborating with other members of the Research Staff to define new LLM research initiativesBroad surveying of literature, evaluating, classifying, and distilling current methodsDesigning and carrying out experimental programs for LLMsDriving transformer (LLM) training jobs successfully on distributed compute infrastructure and deploying new models into productionDocumenting and presenting results and complex technical concepts clearly for a target audienceStaying up to date with the latest advances in deep learning and LLMs, with a particular eye towards their implications and applications within our productsYou'll Love This Role if YouAre passionate about AI and excited about working on state of the art LLM researchHave an interest in producing and applying new science to help us develop and deploy large language modelsEnjoy building from the ground up and love to create new systems.Have strong communication skills and are able to translate complex concepts clearlyAre highly analytical and enjoy delving into detailed analyses when necessary It's Important to Us That You Have3+ years of experience in applied deep learning research, with a solid understanding toward the applications and implications of different neural network types, architectures, and loss mechanismProven experience working with large language models (LLMs) - including experience with data curation, distributed large-scale training, optimization of transformer architecture, and RL LearningStrong experience coding in Python and working with PytorchExperience with various transformer architectures (auto-regressive, sequence-to-sequence.etc)Experience with distributed computing and large-scale data processingPrior experience in conducting experimental programs and using results to optimize modelsIt Would Be Great if You HadDeep understanding of transformers, causal LMs, and their underlying architectureUnderstanding of distributed training and distributed inference schemes for LLMsFamiliarity with RLHF labeling and training pipelinesUp-to-date knowledge of recent LLM techniques and developmentsPublished papers in Deep Learning Research, particularly related to LLMs and deep neural networksBacked by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $85 million in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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At Parallel Web Systems, we are bringing a new web to life: it’s built with, by, and for AIs. Our work spans innovations across crawling, indexing, ranking, retrieval, and reasoning systems. Our first product is a set of APIs for AIs to do more with web data. We are a fully in-person team based in Palo Alto, CA. Our organization is flat; our team is small and talent dense.We want to talk to you if you are someone who can bring us closer to living our aspirational values:Own customer impact - It’s on us to ensure real-world outcomes for our customers.Obsess over craft - Perfect every detail because quality compounds.Accelerate change - Ship fast, adapt faster, and move frontier ideas into production.Create win-wins - Creatively turn trade-offs into upside.Make high-conviction bets - Try and fail. But succeed an unfair amount.Job: Our first dedicated research hire - you will answer the question: how to train and scale a model that can serve a web index?You: Have deep intuition on modern models and training. Like to argue how search, recommendations, and transformer models can converge. You care about your research being applied to product and systems that millions use.Our founder is Parag Agrawal. Previously, he was the CEO and CTO at Twitter. Our investors include First Round Capital, Index Ventures, Khosla Ventures, and many others.

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Somite.ai is a venture-backed company transforming stem cell biology with AI. We recently raised over $47 million in a Series A funding round, bringing our total funding to about $60 million. Just as LLMs revolutionized human language, we’re decoding the language of cells—how they communicate and decide their fate—using vast amounts of in-house generated data. Our AI models enable precise control over cell behavior, unlocking the potential to engineer therapies for diseases like diabetes, neurodegenerative diseases, and muscular dystrophies. Our platform, DeltaStem, accelerates therapy creation and continually improves through data-driven insights.Founded by Dr. Micha Breakstone, a serial AI entrepreneur from MIT, and three Harvard Medical School professors, including the Chair of Genetics, Somite.ai is at the forefront of a new era in healthcare.Location: BostonClick the following links to learn more about Somite:https://x.com/SomiteAi/status/1922284999891472808https://www.forbes.com/sites/gilpress/2025/05/13/somite-ai-raises-47m-series-a-to-reinvent-cell-replacement-therapy/Click the following link to Apply:https://jobs.ashbyhq.com/somite-ai?utm_source=LinkedIn+Manual+PostingAbout the Role:We seek a motivated and experienced molecular biologist to join our team to support development of our novel capsule technology. In this role, you will design, optimize, and execute strategies for custom barcoding and sequencing protocols to advance our understanding of cell differentiation. You will play a critical role in driving platform development, conducting high-throughput experiments, and collaborating cross-functionally with our AI team. This is a hands-on, lab-based position that requires strong technical expertise and the ability to work independently, while contributing to collaborative project goals.Responsibilities:● Design, execute, optimize and interpret platform development experiments● Maintain clear, organized records of experimental design, execution, and outcomes, with attention to detail and data integrity● Communicate findings to leadership● Present findings and experimental progress in internal meetings, adapting communication for both technical and cross-functional audiences● Collaborate closely with colleagues and leadership to advance development to support corporate goals● Share learnings, offer support, and help build a lab culture grounded in accountability, urgency, and team successQualifications:● Ph.D. in Molecular Biology, or a related field, with 5+ years of hands-on experience in single cell sequencing, novel molecular biology in biotechnology settings● Proven success in developing novel technologies● Proficiency in molecular and cell biology techniques, including single cell sequencing● Excellent communication skills, both written and verbal● Detail-oriented with strong documentation and organizational skills and the ability to work independentlyPreferred Qualifications:● Degree concentrations in molecular biology, developmental biology, and/or stem cell biology● Experience with technology development● Highly experienced in single cell sequencing● Prior experience in cell therapies and regenerative medicine● Background in team leadership● Comfortable operating in fast-paced, startup or early-phase biotech environmentsSomite.ai’s Core Values:● We show up – fully accountable, all-in, doing whatever it takes● We act with urgency – swift, decisive, proactive● We support one another – collaborative, helpful, empatheticClick the following link to Apply:https://jobs.ashbyhq.com/somite-ai?utm_source=LinkedIn+Manual+PostingBenefits:● Take a technical leadership role with a mission-driven company with the potential to significantly impact the lives of millions.● Work alongside a talented and passionate team at the forefront of AI and cellular biology.● Contribute to the development of groundbreaking therapies that address significant unmet medical needs.● Enjoy a competitive salary / benefits package and a collaborative work environment.Exceptional candidates who demonstrate outstanding capabilities and potential will be considered, even if they do not meet every qualification listed.Join us and help unlock the full potential of AI for the benefit of human health!

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About the jobMaincode is building sovereign AI models in Australia. We train foundation models from scratch, design new reasoning architectures, and deploy them on state-of-the-art GPU clusters. This is not fine-tuning someone else’s work. This is creating new systems from first principles. We’re hiring a research leader for our AI Residency program. Our AI Residency Program is a focused research collaboration with top academic talent: late-stage PhD students, postdocs, and professors, working on foundational AI research at the architectural level. Each cohort of residents joins us for 6-months to pursue ambitious projects that align with our mission, combining academic rigor with industry-scale infrastructure and execution. This is a full-time, permanent role with ongoing responsibility for sourcing and selecting residents, guiding them through their projects, supporting publication efforts, and ensuring impactful, aligned research outcomes. The program is already up and running, now we’re looking for a research leader to own its day-to-day execution. You’ll make sure the right people are selected, the right projects are pursued, and the research produced is impactful, publishable, and aligned with Maincode’s long-term goals. You’ll also lead sourcing, interviewing, and hiring of residents, and ensure each one’s experience is productive and inspiring. This is a hybrid role based in Australia.What you’ll doRun the AI Residency Program end-to-end, ensuring smooth operations, clear timelines, and high-impact outcomes.Source, recruit, and hire outstanding residents, managing the full candidate pipeline from outreach to signed offers.Select and greenlight projects in consultation with Maincode’s research leadership to ensure strategic alignment.Guide and mentor residents throughout their 6-month program, drawing on your academic and industry experience.Maintain research quality, ensuring outputs meet top-tier publication standards and practical applicability.Coordinate with internal research teams so residency work complements and extends Maincode’s own research agenda.Represent the program externally, building relationships with universities, research groups, and other AI communities. Who you areA senior academic researcher (postdoc or above) with deep expertise in AI and a broad understanding of the field’s directions.Experienced in supervising PhD-level research and managing multiple projects simultaneously.Skilled in candidate sourcing, interviewing, and selection for high-level research roles.Have a strong publication record in top AI/ML venues (NeurIPS, ICLR, ICML, etc.).Strong strategic judgment in choosing projects and people that balance novelty with long-term impact.A confident communicator who can work seamlessly with both academic researchers and industry engineers.Motivated to strengthen sovereign AI capability in Australia through academic–industry collaboration.Why Maincode We are a small, mission-driven team building some of the most advanced AI systems in Australia. We operate our own GPU clusters, run large-scale training, and work closely across research and engineering to push the frontier of what’s possible. You’ll be surrounded by people who:Care deeply about model internals, not just outputs.Build things that work at scale.Take pride in learning, experimenting, and shipping.Believe Australia must have independent, world-class AI systems.If you want to run a program that brings world-class researchers into an environment where they can test ideas at scale and make a lasting impact on the science of AI, we’d love to hear from you.

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About the RoleAt Luma, the Post-training team is responsible for unlocking creative control in the world’s largest and most powerful pre-trained multimodal models. The team works closely with the Fundamental Research team and the Product teams across Luma to train our image and video generative models improving their capabilities in the final step refining them to be better aligned with what our users expect.What You’ll DoOptimize Luma's image and video generative models through targeted fine-tuning to improve visual quality, instruction adherence, and overall performance metrics.Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences and quality standards.Partner closely with the Applied Research team to identify product requirements, understand diverse use cases across Luma's platforms, and execute targeted fine-tuning initiatives to address performance gaps and enhance user-facing capabilities.Conduct comprehensive side-by-side evaluations comparing model performance against leading market competitors, systematically analyzing the impact of post-training techniques on downstream performance metrics and identifying areas for improvement.Develop advanced post-training capabilities for Luma’s video models including Camera control, Object & character Reference, Image & Video Editing, Human Performance & Motion Transfer Approaches.Architect data processing pipelines for large-scale video and image datasets, implementing filtering, balancing, and captioning systems to ensure training data quality across diverse content categories.Research and deploy cutting-edge diffusion sampling methodologies and hyperparameter optimization strategies to achieve superior performance on established visual quality benchmarks.Research emerging post-training methodologies in generative AI, evaluate their applicability to Luma's product ecosystem, and integrate promising techniques into our Post-training recipe.QualificationsAdvanced degree (Master's or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or related technical discipline with concentrated study in deep learning and computer vision methodologies. Demonstrated ability to do independent research in Academic or Industry settings.Substantial industry experience in large-scale deep learning model training, with demonstrated expertise in at least one of Large Language Models, Vision-Language Models, Diffusion Models, or comparable generative AI architectures.Comprehensive technical proficiency and practical experience with leading deep learning frameworks, including advanced competency in one of PyTorch, JAX, TensorFlow, or equivalent platforms for model development and optimization.Strong orientation toward applied AI implementations with emphasis on translating product requirements into technical solutions, coupled with exceptional visual discrimination and dedicated focus on enhancing visual fidelity and aesthetic quality of generated content.Proficiency in accelerated prototyping and demonstration development for emerging features, facilitating efficient iteration cycles and comprehensive stakeholder evaluation prior to production implementation.Established track record of effective cross-functional teamwork, including successful partnerships with teams spanning Product, Design, Evaluation, Applied, and creative specialists.

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About OumiWhy we exist: Oumi is on a mission to make frontier AI truly open for all. We are founded on the belief that AI will have a transformative impact on humanity, and that developing it collectively, in the open, is the best path forward to ensure that it is done efficiently and safely.What we do: Oumi provides an all-in-one platform to build state-of-the-art AI models, end to end, from data preparation to production deployment, empowering innovators to build cutting-edge models at any scale. Oumi also develops open foundation models in collaboration with academic collaborators and the open community.Our Approach: Oumi is fundamentally an open-source first company, with open-collaboration across the community as a core principle. Our work is:Open Source First: All our platform and core technology is open sourceResearch-driven: We conduct and publish original research in AI, collaborating with our community of academic research labs and collaboratorsCommunity-powered: We believe in the power of open-collaboration and welcome contributions from researchers and developers worldwideRole OverviewThe Research Scientist will be an integral part of Oumi's research team, focusing on advancing the state-of-the-art in large language models (LLMs), vision language models (VLMs), and related technologies. This role involves conducting cutting-edge research, contributing to open-source projects, and collaborating with other researchers and engineers. Researchers at Oumi will work on various aspects of LLM/VLM development including training, evaluation, data curation, and benchmark development.What you’ll do:Model Development: Conduct research on training and evaluating new Large language models (LLMs), Vision Language Models (VLMs), and other AI models. This includes exploring new architectures, training techniques, and optimization methods.Data Curation: Develop methodologies for curating high-quality datasets for training and evaluating LLMs. This may involve data synthesis and other novel techniques.Benchmark Development: Develop evaluation benchmarks to measure the performance of LLMs across various tasks and domains.Research and Experimentation: Design and conduct experiments to validate research hypotheses and improve model performance.Open Source Contribution: Contribute to the Oumi open-source platform, models and projects, and other relevant tools and libraries.Collaboration: Collaborate with other researchers, engineers, and the broader community to advance the field of open-source AI.Publication: Publish research findings in leading conferences and journals.Platform Evaluation: Evaluate existing models and identify areas of improvement.Flexibility: Work with various models, including text and multimodal models, and both open and closed models.Problem Solving: Focus on the research that matters by skipping the plumbing and moving straight to research, building on the work of others and contributing back.What you’ll bring:Education: A Ph.D. or MSc. in computer science, machine learning, artificial intelligence, or a related field is preferred. Candidates with a strong publication record, or equivalent industry experience will be considered.Research Experience: Demonstrated experience in conducting original research in machine learning, with a strong publication record in top-tier conferences or journals.ML Expertise: Deep understanding of machine learning and deep learning concepts, with specific knowledge of large language models (LLMs) and/or vision language models (VLMs).Programming Skills: Strong programming skills in Python and experience using deep learning frameworks (e.g. PyTorch).Open Source: Familiarity with open-source projects and a passion for contributing to the open-source community.Initiative: A self-starter who can work independently and take ownership of initiatives.Values: Share Oumi's values: Beneficial for all, Customer-obsessed, Radical Ownership, Exceptional Teammates, Science-grounded.BenefitsCompetitive salary: $100,000 - $220,000Equity in a high-growth startupComprehensive health, dental and vision insurance21 days PTORegular team offsites and events