Research Chemist Jobs

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. Responsibilities: Implement and optimize post-training techniques at scale on frontier models Conduct research to develop and optimize post-training recipes that directly improve production model quality Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation Develop tools to measure and improve model performance across various dimensions Collaborate with research teams to translate emerging techniques into production-ready implementations Debug complex issues in training pipelines and model behavior Help establish best practices for reliable, reproducible model post-training You may be a good fit if you: Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities Adapt quickly to changing priorities Maintain clarity when debugging complex, time-sensitive issues Have strong softwa

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas: Developing systems that enable models to use computers effectively Advancing code generation through reinforcement learning Pioneering fundamental RL research for large language models Building scalable RL infrastructure and training methodologies Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. 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 positi

About SAI Group SAI Group is a private investment firm dedicated to incubating and scaling AI-powered enterprise software companies. Our portfolio spans across rapidly growing businesses that serve over 2,000 global customers, generating nearly $600 million in annual revenue and employing over 4,000 individuals worldwide. As we continue to scale, we are focused on building world-class teams to drive our portfolio companies' success. Role Overview: As a Research Engineer, you will be instrumental in exploring and establishing best practices for leveraging and extending novel Generative AI based technologies to develop groundbreaking solutions for enterprise use cases. This role offers a unique opportunity to delve into the rapidly evolving world of foundation models, AI agents, reasoning models etc. and contribute to the design and development of an innovative enterprise AI platform to deliver transformative, AI-enabled work experiences for enterprise users. What You Will Do Experimentation and Research : Systematically explore various technologies and strategies such as foundation models, agentic workflows, ontology and knowledge graphs, reinforcement learning, dynamic prompting, retrieval augmented generation, and collaborative problem solving to enhance our understanding and utilization of foundation models and related Generative AI frameworks. You will design and conduct experiments to probe the limits and capabilities of different foundation models, frameworks and their application strategies. Development and Analysis : Design experiments to understand the capabilities and limits of foundation models. Build tools necessary for conducting experiments, run these experiments, and meticulously analyze the results. Build on the quantitative and qualitative findings from these experiments to design future experiments and shape the architecture of our enterprise AGI platform. Prototyping and Innovation : Take charge of developing and

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. 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 and may be inclusive of several career levels at Scale; it will be determined du

About Scale At Scale AI, 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 abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

About Karya : Why was Karya on the cover of the Time Magazine , highlighted by Satya Nadella , and chosen by Google as its partner for Project Vaani ? In part, because Karya is on a mission to provide AI enabled earning and learning opportunities to economically underserved communities, thereby building a pathway out of poverty for them. Karya achieves this while also delivering high quality, timely, and price competitive data to its clients. Karya’s workers make at least 20 times the Indian minimum wage and through our one-of-a-kind digital work platform, we have delivered over 40 million digital tasks and are poised to positively impact over 100 thousand workers by the end of the year. In the coming years, our goal is to rapidly scale our impact by bringing economic opportunities to millions of underserved users in India. Key Responsibilities Quantitative Research: Index Development: Support design and development of socio-economic indices using unit-level datasets. Impact Estimation: Statistical impact assessment using statistical software such as R or Stata, including Randomized Controlled Trials (RCT) or quasi-experimental methods. Sample Size Estimation: Calculate and validate appropriate sample sizes for surveys and impact assessments. Survey Tool Development: Design survey tools tailored for social and development sector projects. Data Handling: Experience extracting and work with development sector datasets (NFHS, PLFS, etc.), or demonstrate a strong desire to learn and apply these data sources. Data Validation: Validate and triangulate survey data using robust methodologies. Mixed Methods: Combine qualitative and quantitative research approaches to ensure comprehensive analysis. Publications (Preferred): Candidates with prior publications will be given preference. Internal Monitoring & Data Management: Stakeholder Collaboration: Work closely with cross-functional teams to co-develop Key Performance Indicators (KPIs)

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: We are looking for Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs! Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures. Responsibilities: Designing and implementing from scratch new information architecture strategies Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data Designing and evaluating advanced agentic search capabilities. You may be a good fit if you: Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using Have good machine learning research experience Have experience developing software that utilizes Large Language Models such as Claude Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to partner with world-class ML researchers to develop new LLM capabilities Care about the societal impacts of your work Have clear written and verbal communication Strong candidates will also have experience with: Collaborating with product teams to quickly prototype and deliver innovative solutions Building complex agentic systems that utilize LLMs Developing scalable d

About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We are looking for an experienced Research Engineer to work on retrieval & search problems across our API and ChatGPT. As the AI landscape has evolved over the last few years, retrieval & search have emerged as key use cases for our models, and we are investing in ensuring that we can offer these search-based product experiences for our users. You will be at the center of our retrieval & search efforts as a company, and the progress you drive here will reach millions of end users. In this role, you will: Work on retrieval & search algorithms and methodologies in close collaboration with our research team, including problems in such domains as document search, enterprise search, knowledge retrieval, and web-scale search. Deploy these search methodologies into production in both the API and ChatGPT to be used by millions of end users. Explore novel research topics in retrieval & search that may inform our product strategy in the medium and long term. Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world You might thrive in this role if you: Have extensive prior experience building and maintaining production machine learning systems. Have prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases Have prior experience building and iterating on internet-scale search systems Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done Have the ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or de

About the Role As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competi

About the Team The Product Policy team develops and implements policies that shape how OpenAI’s technology is built and used. We work with teams across the company to turn complex questions about AI’s benefits and risks into practical guidance for responsible research, product development, and deployment. About the Role As Research Lead, Policy Communications, you will build and lead a rigorous research program that helps OpenAI understand how people engage with complex AI policy issues. You will design qualitative and quantitative studies, develop durable research practices, and translate findings into clear recommendations for Policy, Communications, Product, and other partners. Your work will help teams communicate complex topics accurately, responsibly, and in ways that are useful to a broad range of audiences. This role can be based in San Francisco or Remote. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You’ll be responsible for: Build and manage a mixed-methods research program from initial questions through study design, fieldwork, analysis, reporting, and documentation. Establish high standards for quality, consistency, and responsible research practice. Design rigorous quantitative research, including surveys and longitudinal studies. Oversee questionnaire design, sampling, weighting, vendor quality, analysis, and clear communication of uncertainty and limitations. Lead qualitative research, including interviews and focus groups, to understand how people interpret complex policy topics. Use these insights to improve the clarity, accuracy, and usefulness of policy communications. Turn findings into executive-ready reports with practical recommendations for Policy, Communications, Product, Marketing, Data Science, Legal, Privacy, and other partners. Build reusable research tools, benchmarks, and knowledge that strengthen decision-making over time. We’re looking for someone with: We’re looking f

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pretraining team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Key Responsibilities: Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development Independently lead small research projects while collaborating with team members on larger initiatives Design, run, and analyze scientific experiments to advance our understanding of large language models Optimize and scale our training infrastructure to improve efficiency and reliability Develop and improve dev tooling to enhance team productivity Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications: Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field Strong software engineering skills with a proven track record of building complex systems Expertise in Python and experience with deep learning frameworks (PyTorch preferred) Familiarity with large-scale machine learning, particularly in the context of language models Ability to balance research goals with practical engineering constraints Strong problem-solving skills and a results-oriented mindset Excellent communication skills a

Become a part of our caring community Humana’s Quality and Cost Strategy Analytics Team is seeking a Research Scientist 2 (Remote). Healthcare is rapidly changing, and our members are living longer, often with more chronic conditions. The Quality and Cost Strategy Analytics team identifies opportunities and build solutions to improve clinical outcomes and lower costs for millions of Medicare Advantage beneficiaries leveraging data science & analytics, clinical expertise, strategic mindset, and rigorous study designs. In this multi-disciplinary team, you will have the opportunity to work closely with strategy partners and clinicians to shape Humana’s future enterprise clinical strategies and initiatives. The Research Scientist 2 will lead research, evaluation and development of opportunities that optimize healthcare delivery, lower medical cost while improve member health outcomes, through applying mathematical, statistical, epidemiologic and data science methods. The Research Scientist 2 will also partner with stakeholders across the enterprise to identify, prioritize and measure the impact of core and novel solutions to significant problems in healthcare and improve the health of especially underserved population, using high volumes of structured and unstructured data. Responsibilities As a Research Scientist 2, you will: Research, prototype and scale new ideas to improve population health and healthcare delivery Collaborate with analytic and business teams to set objectives, approaches, and work plans Collaborate with strategy to evaluate existing programs and identify and measure new solutions to impact healthcare Leverage a wide range of analytics methods ranging from descriptive to prescriptive to transform high volumes of complex data into analytics solut

US Equity Strategy Strategist Citi Research has an opening for an Equity Research Analyst to join its US Equity Strategy team. This is a demanding role requiring exceptional analytic skills along with the ability to work independently as well as part of a small team. The individual will take ownership of several processes critical to our published work. You will produce high-impact analysis of equity markets and investment themes incorporated in the advice which Citi delivers to both internal and external clients worldwide. In this role, we expect you will develop into a subject matter expert on US equity markets. This is an opportunity to make a direct and measurable contribution to our research product and be an integral part in developing our US equity market calls and insight. Responsibilities Build, maintain, and enhance financial databases and models that support ongoing and bespoke research needs. Assess macro and micro economic forces at work and incorporate into our market views. Analyze global equity markets and financial trends to produce timely, well-reasoned investment insights that inform client decisions and support Citi's broader research output. Author high-quality research reports and thematic pieces that clearly communicate Citi's investment views to external clients and internal stakeholders. Originate and develop analysis of US investment themes, contributing to US Equity Strategy product Deliver tailored analysis and data-driven responses to requests from investors and Citi colleagues, ensuring accuracy and relevance to their specific needs. Collaborate closely with Citi Research professionals across regions and disciplines to ensure a consistent, globally informed perspective in all published work. Uphold the highest standards of risk awareness and professio