Research Chemist Jobs

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

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. Research Scientist SpaceXAI is building the future of coding. We train frontier coding agents and scale RL on real user data to make them increasingly effective. About the role We’re looking for Research Scientists who can drive effective RL or mid-training research in a small-team setting. You’ll own ambiguous, hard research problems end-to-end: forming hypotheses, designing experiments, building the training/eval/data needed to test them, and pushing results into the next model. You should expect significantly more scope and autonomy than in other research labs. What you’ll do Improve our understanding of RL, what it takes to handle longer horizon tasks, and train with less compute Train graders to improve performance on coding tasks with non-verifiable reward Improve the quality and difficulty of datapoints we use for training our models Realtime RL for coding agents You may be a fit if You have a deep background in RL and strong machine learning fundamentals You’re an excellent programmer and software engineer You can handle ambiguous research tasks with little guidance You care a lot about data quality, and can dive into the data when appropriate You are truth seeking, aimi

About the Team The Human Data team at OpenAI is responsible for identifying and mitigating risks in advanced AI systems by designing evaluations, surfacing vulnerabilities, and collaborating closely with researchers to strengthen model reliability and public trust. About the Role As a Research Program Manager, you will lead initiatives that test the safety and robustness of OpenAI’s models through creative experimentation and structured evaluation. You’ll coordinate efforts across research and engineering teams to transform ambiguous risks into concrete research programs and influence future model development and deployment. We’re looking for people who are technically savvy, comfortable with ambiguity, and excited about shaping the future of safe AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead programs that explore unexpected model behaviors and identify failure modes. Translate vague or emergent risk signals into clear priorities and actionable research plans. Design and run creative evaluations, experiments, and red-teaming campaigns. Collaborate with research, product, and deployment teams to integrate findings into model training and deployment cycles. Develop repeatable systems for tracking model performance and understanding emerging behavior patterns. You might thrive in this role if you: Have strong experience in technical program management, with excellent organizational and communication skills. Are familiar with large language models, prompt engineering, or model evaluation techniques. Are comfortable managing fast-paced, high-uncertainty projects and shaping them from the ground up. Are creative and resourceful in devising new methods for testing model behavior and performance. Can effectively coordinate across technical and non-technical stakeholders to drive alignment and execution. About OpenAI OpenAI is an AI resear

About the Team OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops. About the Role We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world. We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security. Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks. Design and iterate on user-facing tools and backend services to support high-quality data workflows Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal r

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 As an Economist at Anthropic, you will work to measure and understand AI's effects on the global economy. You will make fundamental contributions to the development of the Anthropic Economic Index, establishing new methodologies to measure the usage, diffusion, and impact of AI throughout the economy using privacy-preserving tools and novel data sources. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Responsibilities Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including quarterly reports and industry-specific deep dives Design and conduct empirical research on AI's economic effects, drawing on external data sources and the privacy-preserving measurement systems internally Develop new methodological approaches for studying AI's impact on: Labor markets and the future of work Productivity and task transformation Economic inequality and displacement Industry-specific disruption and adaptation Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios D

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're looking for a research engineer who believes that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. On the Vision team, you'll own the end-to-end process of creating training data and RL environments targeting visual knowledge work: identifying long-horizon and vision-heavy tasks, building evals, designing rewards, and scaling data. This is a unique role that combines applied research with hands-on data work. It's also highly collaborative — you'll partner with external vendors, pretraining, RL, and product teams to make sure the environments you build translate into real-world knowledge work capabilities. What you'll do: Own the data strategy for vision capabilities end-to-end, from building evals and scaling RL environments Manage technical relationships with external data vendors, including writing task specifications, evaluating visual data and annotation quality, and iterating on reward design Develop and improve QA frameworks that catch reward hacking and ensure environment quality at scale Run generalization experiments to measure how data strategy changes improve multimodal capabilities on held-out evaluations Partner with pretraining, RL, and product teams, and do the science that shows we’re all rowing in the same direction You may be a good fit if you: Have 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects Have experience with reinforcement learning, reward design, or training data curation for large language or vision-language models Are familiar with the architecture, training, and operation of large visi

A discretionary macro investment team is looking to add a fundamental analyst/strategist in rates and FX, focused primarily on Southeast Asian emerging markets. What you’ll do Work with PM to formulate and develop trade ideas across Southeast Asian FX and rates markets Develop and maintain sell-side relationships Assist in portfolio and risk management Conduct ongoing fundamental research to support and enhance the investment activities of the group Work on numerous ad-hoc projects to enhance the trade identification and management process Work with banks and brokers for information gathering, relationship building and assisting with execution What’s required 10-12 years of experience in fixed income in a strategy or analyst role at a top tier hedge fund, asset manager, or bank Highly knowledgeable about Southeast Asian emerging markets Knowledge and ability to work throughout the trade-cycle: completing risk-assessment analysis, trade structuring and implementation to the point of execution Deep understanding of technical details and idiosyncrasies related to the fixed income markets in these countries Strong competency in Excel and VBA, and preferably strong programming skills in a common language such as Python Strong communicator who values building relationships with colleagues and stakeholders, and able to significantly raise but also modulate volume depending on opportunity set Willingness to take ownership of his/her work, working both independently and within a small team Commitment to the highest ethical standards We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provide: Health care benefits Generous parental and family leave policies Mental and physical wellness programs Volunteer opportunities Support for employee-led affinity groups representing women, people of color and the LGBT+ community Tuition assistance About Point72 Point72 is a leading global alternative investment fir

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 build the safety and oversight mechanisms that govern how our models handle biological knowledge. As a bio safety researcher, you will spend your time: designing and running capability evaluations against frontier models, generating and curating training data for our safety classifiers, training and iterating on those classifiers alongside our ML engineers, and measuring how they hold up against adversarial pressure in production traffic. This work sits at the intersection of applied ML and biosecurity. You will help define what responsible AI safety looks like in the biological domain, translating threat models into evals, datasets, and deployed systems. The core technical tension you will own is precision: safeguards need to be robust against sophisticated actors while staying out of the way of the far larger population of legitimate researchers using Claude to accelerate life sciences work. Getting that tradeoff right is an empirical problem, and you will be the person measuring it. You do not need to be an ML researcher today. We are looking for strong scientific programmers with real depth in modern biology who want to bring that depth to bear on model evaluation and classifier development. Key responsibilities Design, build, and run capability evaluations to assess what new models can do in the biological domain, and turn results into concrete deployment recommendations Develop training and evaluation datasets for our safety classifiers, working with internal and external threat modeling experts to ground them in realistic risk Train, tune, and iterate on safety classifiers

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Staff Research Engineer, you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on avatar-centric interactive video diffusion models. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 60,000 businesses. This is a unique opportunity for experts in machine learning and diffusion models to shape the future of AI video agents that can think, act, and react like humans. As part of our Interactive Avatars Team, you’ll work on cutting-edge research with a clear focus on turning breakthrough ideas into real product capabilities. You’ll join a team that moves fast, iterates often, and builds models that ship and make a meaningful impact. Example tasks and responsibilities include: Adapt diffusion models to incorporate diverse conditioning signals (e.g., audio, motion, interaction cues). Develop methods for streaming infinitely long video sequences at real-time rates. Work on the perceptual layer of interactive agents, including understanding user audio and generating appropriate contextua

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role The Data team manages the complete lifecycle of data for researchers - from sourcing and large-scale processing to delivering datasets that power our models. Data sits at the heart of our Research efforts and enables all other teams. As part of the Data team, you’ll work with over a million hours of video and audio data. This role exists at the intersection of applied research, data engineering, and ML infrastructure rather than being a traditional research position . You’ll build the world’s best human-centric data lake by collaborating closely with our model training teams. By understanding their requirements, you’ll extract new features and annotations that elevate our datasets. You should be passionate about enhancing model performance through high-quality, accurate datasets. Our infrastructure and pipelines are in great shape, and this role provides room to not only enhance them but also influence the team’s longer-term strategy. What we're looking for: A strong background in data-centric, applied Machine Learning, with hands-on experience improving model performance through data quality, curation, labeling, and evaluation rather than model architecture alone Experience working on the data la

About us EVERY™ is a leading VC-backed food tech ingredient company and market leader using precision fermentation to create animal proteins without the animal for the global food and beverage industry. EVERY™ is a team of passionate change-makers who are reimagining the factory farm model with a kinder, more sustainable alternative. Leveraging precision fermentation to produce hyper-functional and one-to-one replacement proteins from microorganisms, EVERY™ is on a mission to decouple the world’s proteins from the animals that make them. We are a passionate, determined (and fun!) team with a vital objective, and we're on the lookout for like-minded people to join our mission. For more information, visit www.every.com The Role: This unique entry-level Research Associate I position offers the rare chance to work across two core teams, Analytics and Protein Science. You’ll gain hands-on experience supporting protein development, purification, and analysis, while learning how these disciplines work together to drive innovation in precision fermentation. This is a great opportunity for someone early in their career who thrives in the lab, loves variety, and wants to learn fast in a collaborative, mission-driven environment. What you'll accomplish Generate data through basic biochemistry/molecular biology techniques (including but not limited to BCA, SDS-PAGE) Operate and maintain analytical equipment (e.g., HPLC-UV/RI and Combustion Analyzer, dynamic light scatterer, FPLC-UV, fluorescence/UV plate reader) Support protein characterization workflows through lab-scale protein powder generation involving bench-scale downstream processing unit operations (microfiltration, ultrafiltration, diafiltration) Prepare samples, reagents, and buffers to support cross-functional experiments Collaborate with scientists and engineers across teams to troubleshoot and iterate quickly as part of our Design, Build, Test, and Learn pipeline Present results

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Senior Research Engineer, you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on avatar-centric interactive video diffusion models. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 60,000 businesses. This is a unique opportunity for experts in machine learning and diffusion models to shape the future of AI video agents that can think, act, and react like humans. As part of our Interactive Avatars Team, you’ll work on cutting-edge research with a clear focus on turning breakthrough ideas into real product capabilities. You’ll join a team that moves fast, iterates often, and builds models that ship and make a meaningful impact. Example tasks and responsibilities include: Adapt diffusion models to incorporate diverse conditioning signals (e.g., audio, motion, interaction cues). Develop methods for streaming infinitely long video sequences at real-time rates. Work on the perceptual layer of interactive agents, including understanding user audio and generating appropriate contextu

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 Horizons The Horizons team leads Anthropic's reinforcement learning (RL) research and development, playing a critical role in advancing our AI systems. We've contributed to every Claude release, with significant impact on the autonomy, coding, and reasoning capabilities of Anthropic's models. About the role We're hiring for the Cybersecurity RL team within Horizons. As a Research Engineer, you'll help to safely advance the capabilities of our models in secure coding, vulnerability remediation, and other areas of defensive cybersecurity. This role blends research and engineering, requiring you to both develop novel approaches and realize them in code. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers, engineers, and cybersecurity specialists across and outside Anthropic. The role requires domain expertise in cybersecurity paired with interest or experience in training safe AI models. For example, you might be a white hat hacker who's curious about how LLMs could augment or transform your work, a security engineer interested in how AI could help harden systems at scale, or a detection and response professional wondering how models could enhance defensive workflows. You may be a good fit if you: Have experience in cybersecurity research. Have experience with machine learning. Have strong software engineering skills. Can balance research exploration with engineering implementation. Are passionate about AI's potential and committed to developing safe and beneficial systems

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have a working knowledge of relevant models, and building evaluations for model capability improvement. Are comfortable diving into a large ML codebase to debug. Thrive in a dynamic and technically complex environment. 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

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: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we're trying to "reverse engineer". A few places to learn more about our work and team at a high level are this introduction to Interpretability from our research lead, Chris Olah ; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team's notable publications include A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , Toy Models of Superposition , Scaling Monosemanticity , and our Circuits’ Methods and Biology papers. This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . We aim to create a solid foundation for mechanisticall