AnthropicRemote-Friendly (Travel Required) | San Francisco, CA
Remote Full-time
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Qualifications
We are seeking an individual with a strong background in AI research, particularly in reinforcement learning and reward modeling. You should possess a profound understanding of large language models and experience in developing training methodologies. Strong analytical skills and the ability to design experiments focused on model generalization and robustness are essential. Familiarity with Python is a must, as all interviews will be conducted in this language. The ideal candidate will have a proven track record of leading ambitious research projects, contributing to publications, and mentoring junior researchers to foster organizational knowledge.
About the job
Join Anthropic as a Senior Research Scientist on our Reward Models team, where you will spearhead groundbreaking research aimed at enhancing our understanding of human preferences at scale. Your innovative contributions will directly influence how our AI models, including Claude, align with human values and optimize for user needs. You will delve into the forefront of reward modeling for large language models, designing novel architectures and training methodologies for Reinforcement Learning from Human Feedback (RLHF). Your research will explore advanced evaluation techniques, including rubric-based grading, and tackle challenges such as reward hacking. Collaboration is key, as you'll work alongside teams in Finetuning, Alignment Science, and our broader research organization to ensure your findings result in tangible advancements in AI capabilities and safety. This role offers you an opportunity to address critical AI alignment challenges, leveraging cutting-edge models and substantial computational resources to further the science of safe and capable AI systems.
About Anthropic
At Anthropic, our mission is to engineer AI systems that are not only reliable and interpretable but also capable of being steered towards beneficial outcomes for users and society. We are rapidly expanding our team of dedicated researchers, engineers, policy experts, and business leaders, all working together to create AI solutions that prioritize safety and utility. Join us in our journey to redefine the possibilities of AI for the greater good.
Team focus The Alignment Science team at OpenAI works on intent alignment for artificial intelligence. Their goal is to develop models that accurately interpret and follow user requests, while maintaining high standards for safety and transparency. As AI models become more advanced, the team prioritizes keeping them honest about their capabilities and limita…
Join Our Innovative TeamAt OpenAI, our Alignment team is committed to building AI systems that prioritize safety, trustworthiness, and alignment with human values, even as these systems evolve and grow in complexity. We are at the forefront of AI research, developing advanced methodologies to ensure that AI adheres to human intent across diverse scenarios, including high-stakes and adversarial environments. Our focus is on tackling the most critical challenges, addressing areas where AI can have profound impacts. By quantifying risks and making meaningful improvements, we aim to prepare our models for the complexities of real-world applications.Our approach is built on two foundational pillars: (1) integrating enhanced capabilities into alignment, ensuring our techniques evolve positively with increasing capabilities, and (2) centering human input through the development of mechanisms that allow humans to communicate their intent and effectively monitor AI systems, even in intricate situations.Your Role in Shaping the FutureAs a Research Engineer / Scientist on our Alignment team, you will play a pivotal role in ensuring our AI systems align with human intent in complex and unpredictable contexts. Your responsibilities will include designing and implementing scalable solutions that maintain alignment as AI capabilities expand, while incorporating human oversight into AI decision-making processes.This position is based in San Francisco, CA, and follows a hybrid work model of three days in the office each week. We also offer relocation assistance to new team members.Key Responsibilities:Develop and assess alignment capabilities that are context-sensitive, subjective, and challenging to quantify.Create evaluations to accurately measure risks and alignment with human values and intentions.Construct tools and evaluations to examine model robustness across various scenarios.Design experiments to explore how alignment scales with compute resources, data, context lengths, actions, and adversarial influences.Innovate new Human-AI interaction frameworks and scalable supervision methods that enhance human engagement and understanding of AI systems.
About AnthropicAt Anthropic, we are driven by our mission to develop reliable, interpretable, and steerable AI systems. Our commitment is to ensure that AI is safe and beneficial not only for our users but also for society as a whole. Our rapidly expanding team comprises dedicated researchers, engineers, policy specialists, and business leaders collaborating to create impactful AI technologies.About the Role:As a Research Engineer focusing on Alignment Science, you will design and execute sophisticated machine learning experiments aimed at understanding and guiding the behavior of advanced AI systems. Your passion lies in making AI systems helpful, honest, and safe, particularly in the face of challenges posed by human-level capabilities. You embody both the scientific and engineering mindsets. In this role, you will engage in exploratory research on AI safety, concentrating on risks associated with future powerful systems (such as those classified as ASL-3 or ASL-4 under our Responsible Scaling Policy), often working in collaboration with teams focused on Interpretability, Fine-Tuning, and the Frontier Red Team. Discover more about our current research topics and insights on our blog, as we delve into pressing issues such as:Scalable Oversight: Innovating techniques to ensure that highly capable models remain helpful and truthful, even as they exceed human-level intelligence.AI Control: Developing strategies to maintain the safety and harmlessness of advanced AI systems in novel or adversarial environments.Alignment Stress Testing: Implementing rigorous testing frameworks to evaluate AI alignment under various conditions.
About Our TeamThe Alignment Training team at OpenAI focuses on understanding how advanced models develop lasting behavioral patterns throughout the training process. We investigate which behaviors can be influenced during the pre-training, mid-training, and post-training phases; create the necessary data, objectives, and evaluations to guide these behaviors; and assess whether the resulting actions represent a general capability or a byproduct of the training environment.Our research encompasses synthetic data development, various training stages, model behavior analysis, and performance evaluation. We explore how models grasp user intentions, adhere to instructions, reason effectively, demonstrate honesty, and maintain reliability in novel situations. Our ultimate aim is to foster desirable behaviors early in training, reinforce them throughout, and ensure their consistency in real-world applications.About This PositionWe are seeking a seasoned researcher with profound expertise in large-scale model training, synthetic data creation, or evaluation processes, who is passionate about exploring how training decisions influence aligned behaviors in state-of-the-art models.In this role, you will define the research agenda for alignment training: outlining the behaviors we aspire for models to acquire, designing data and training strategies to cultivate them, and developing evaluation mechanisms to verify the breadth, strength, and durability of those behaviors. The ideal candidate will excel at translating vague behavioral inquiries into structured experimental plans: devising hypotheses, creating interventions, establishing pipelines, conducting experiments, and analyzing results for authenticity.This position is particularly suited for individuals eager to engage closely with the core model training framework, where decisions regarding data, objectives, and evaluations critically influence the alignment of deployed systems.Key Responsibilities:Innovate synthetic data methods that instill higher-level behavioral tendencies in models, such as comprehending user intent, consistently following instructions, clear reasoning, honesty, and alignment with defined goals and constraints.Analyze the impact of pre-training, mid-training, and post-training on subsequent model behavior, identifying the most effective interventions for each phase.Develop evaluation loops that link model behavior back to training data and objectives, enabling quicker iterations and clearer feedback.
About Our TeamThe Future of Computing Research team is a dynamic applied research unit within the Consumer Devices group at OpenAI. We are dedicated to pioneering innovative methods, models, and evaluation frameworks that propel our vision for the future of computing. Our focus lies at the cutting edge of multimodal AI, transforming emerging model capabilities into product experiences that are not only functional and enjoyable but also foster long-term trust.Our research delves into a new generation of AI systems capable of learning and evolving over time, adapting to individual needs, and enhancing daily life. This includes exploring long-term memory, user modeling, and personalized systems aligned with broader human goals, values, and overall well-being.We collaborate closely across multiple disciplines—research, engineering, design, product management, and safety—to define what it means to build AI systems that recognize and respond to user needs in a contextually aware and respectful manner, ensuring demonstrable benefits.About the PositionWe are seeking a passionate Research Engineer/Scientist to join our Future of Computing Research team, focusing on Reinforcement Learning from Human Feedback (RLHF) and post-training techniques for personalized multimodal AI systems.In this role, you will be instrumental in establishing the learning and evaluation foundations necessary for models to become increasingly context-aware, adaptive, and useful over time. You will tackle challenges such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that are required to make high-quality behavioral decisions in real-world settings. Our success is measured not just by improved benchmark performance but by enhanced model behavior in actual use cases.The ideal candidate is enthusiastic about advancing beyond simplistic one-turn assistant interactions towards systems that learn and grow through feedback, utilizing richer signals and training against meaningful notions of user value. This requires a thoughtful approach to reward design, feedback mechanisms, and evaluation frameworks that assess the long-term benefits of interventions.This position is based in San Francisco, CA, with a hybrid work model of four days in the office each week. We also provide relocation assistance for new hires.Key Responsibilities:Develop RLHF and post-training strategies for multimodal models.Create reward models and preference-learning pipelines to foster adaptive, personalized model behavior.Engage in long-term evaluation and policy refinement to enhance user interactions.
About Our TeamThe Alignment team at OpenAI is dedicated to ensuring our AI systems are capable of recursive self-improvement while consistently aligning with human intents in complex real-world scenarios. We focus on developing AI that avoids catastrophic outcomes, remains controllable, auditable, and fundamentally aligned with human values as our technological capabilities grow.About the PositionWe are seeking a skilled Program Manager to enhance OpenAI’s alignment and safety initiatives through effective program execution, relationship management, and operational leadership. This role involves close collaboration with alignment leadership to manage key external programs and partnerships, streamline coordination among collaborators, and address ongoing operational needs in a dynamic research environment.This position is based in San Francisco, CA, following a hybrid work model of three days in the office each week. We also provide relocation assistance for new hires.Key Responsibilities:Manage logistics and execution for alignment-related events, coordinating with researchers, external participants, and internal stakeholders.Act as the operational liaison for third-party collaborations, overseeing program management, contract coordination, follow-up, and cross-functional tracking.Foster and oversee external collaborations within the alignment ecosystem, including research partnerships related to misalignment or shared infrastructure initiatives.Assist in recruiting for alignment ecosystem roles by sourcing, mapping, and engaging with trusted candidates and communities.Serve as the Program Manager counterpart for the Alignment blog, facilitating publishing operations, editorial coordination, and drafting support as needed.Support compute management processes for the team, ensuring consistent coordination, tracking, and operational follow-up.If the pilot program succeeds, oversee the Safety Fellows program from start to finish, including the selection process, participant support, programming, and operational management.Ideal Candidate Profile:Possess 4+ years of experience in program management, operations, partnerships, or related fields within research, policy, or technical environments.Demonstrate excellent organizational and multitasking skills, with a keen ability to work in fast-paced environments.Show strong interpersonal skills and a commitment to collaborative teamwork.
Full-time|Hybrid|San Francisco, CA | New York City, NY
Role Overview Anthropic is hiring a Technical Program Manager focused on Alignment. This role centers on guiding projects that help keep AI systems safe and beneficial. The position is based in either San Francisco, CA or New York City, NY. What You Will Do Oversee alignment-related projects, ensuring they move forward smoothly and meet safety objectives. Work closely with teams across disciplines to set project scopes and define clear timelines. Coordinate initiatives that support Anthropic’s strategic direction for AI safety and benefit.
Join Our Impactful TeamAt OpenAI, our UX Research team plays a pivotal role in shaping the future of AI technology. We are a dynamic group dedicated to bridging the gap between users, product innovation, and safety, ensuring that our advanced AI systems are designed with responsibility and genuine human needs in mind.Our insights are crucial in guiding product decisions at OpenAI. We collaborate closely with product managers, designers, engineers, and leadership, tackling complex challenges in rapidly evolving environments where best practices are still in the process of being established.This position is located in San Francisco, CA, and follows a hybrid work model, requiring three days in the office each week. Relocation assistance is available for qualified candidates.Your Role and Responsibilities:Conduct and implement quantitative research throughout the product lifecycle, from foundational insights to concept validation, prototyping, and usability assessments.Collaborate with cross-functional teams, including product managers, designers, engineers, and data scientists, to pinpoint high-impact areas where quantitative insights can significantly influence product strategies.Lead comprehensive, tailored studies that address both strategic and tactical inquiries, employing methodologies such as surveys, experimental designs, and behavioral data analysis.Translate intricate data findings into clear, actionable recommendations that foster alignment and drive decision-making across diverse teams.Utilize strong survey methodologies and statistical rigor to ensure research outcomes are valid, reliable, and ready for decision-making.Shape product strategy through effective cross-functional collaboration and compelling storytelling tailored for various audiences.Ideal Candidate Profile:5+ years of experience in user experience research, market research, data science, or related fields, with a strong emphasis on quantitative methods.Proficient in quantitative research techniques, including statistical analysis, experimental design, survey methodologies, and behavioral data assessment.Advanced data analysis capabilities utilizing tools such as SQL and Python.Exceptional communication skills, both written and verbal, with a proven ability to influence decision-making across all levels of an organization.Demonstrated experience leading impactful quantitative research projects that have significantly influenced product and design decisions.Familiarity with engaging senior stakeholders effectively.
Remote|Remote|Remote-Friendly (Travel Required) | San Francisco, CA
Join Anthropic as a Senior Research Scientist on our Reward Models team, where you will spearhead groundbreaking research aimed at enhancing our understanding of human preferences at scale. Your innovative contributions will directly influence how our AI models, including Claude, align with human values and optimize for user needs. You will delve into the forefront of reward modeling for large language models, designing novel architectures and training methodologies for Reinforcement Learning from Human Feedback (RLHF). Your research will explore advanced evaluation techniques, including rubric-based grading, and tackle challenges such as reward hacking. Collaboration is key, as you'll work alongside teams in Finetuning, Alignment Science, and our broader research organization to ensure your findings result in tangible advancements in AI capabilities and safety. This role offers you an opportunity to address critical AI alignment challenges, leveraging cutting-edge models and substantial computational resources to further the science of safe and capable AI systems.
Join Our Innovative Research at AlljoinedAlljoined is a cutting-edge biotech startup pioneering research in understanding human cognition through EEG technology. We are currently looking for enthusiastic study participants in San Francisco to help us in this exciting venture.Study DetailsParticipants will wear a comfortable, non-invasive EEG cap while seated at a computer. You will be shown a series of images and videos, followed by simple questions. The EEG device monitors brain activity without causing any discomfort to the participant.Eligibility CriteriaAges 18 to 55Willingness to sit for extended periodsProficient in EnglishAvailability for a total of 5 sessionsNo dreadlocks, braids, wigs, or hairstyles incompatible with EEG equipmentLocationLocated in Inner Richmond, San Francisco, CASession DurationEach session will last approximately 2.5 hours (please allocate up to 3 hours for each visit).CompensationParticipants will receive $20 per hour for their involvement.
About MercorMercor sits at the forefront of labor markets and artificial intelligence research, collaborating with premier AI laboratories and enterprises to harness the human intelligence crucial for AI evolution.Our expansive talent network empowers the training of cutting-edge AI models, akin to how educators impart knowledge to students—sharing insights, experiences, and contexts that transcend mere code. Currently, our network comprises over 30,000 experts, generating collective earnings exceeding $2 million daily.At Mercor, we are pioneering a unique category of work where expertise fuels AI progress. Realizing this vision necessitates a bold, fast-paced, and deeply dedicated team. You will collaborate with researchers, operators, and AI firms that are at the vanguard of transforming systems that redefine society.As a profitable Series C company, Mercor is valued at $10 billion and maintains an in-office presence five days a week at our new headquarters in San Francisco.About the RoleIn your capacity as a Research Engineer at Mercor, you will operate at the intersection of engineering and applied AI research. You will play a pivotal role in post-training and Reinforcement Learning from Human Feedback (RLVR), synthetic data generation, and large-scale evaluation workflows essential for advancing frontier language models.Your contributions will help train large language models to adeptly utilize tools, exhibit agentic behavior, and engage in real-world reasoning within production environments. You will be instrumental in shaping rewards, conducting post-training experiments, and constructing scalable systems to enhance model performance. Your responsibilities will also include designing and evaluating datasets, creating scalable data augmentation pipelines, and developing rubrics and evaluators that expand the learning potential of LLMs.
Full-time|$122K/yr - $170K/yr|Remote|Remote ; San Diego, California, United States; South San Francisco, California, United States
Join Veracyte, a leader in transforming cancer care through innovative diagnostics that empower patients and clinicians alike. At Veracyte, we provide an inspiring work environment where you can make a significant impact on patients' lives while advancing your career. Our culture, known as the Veracyte way, emphasizes collaboration, resilience, and a commitment to excellence.Our Core Values:We Seek A Better Way: We boldly innovate and learn from challenges to improve cancer care.We Make It Happen: We prioritize urgency, quality, and enjoyment in our work.We Are Stronger Together: We foster open collaboration and celebrate our collective successes.We Care Deeply: We honor our diverse backgrounds and support each other in doing what is right.The Role:We are on the lookout for an enthusiastic Bioinformatics Research Scientist to join our Translational Bioinformatics group within the Bioinformatics and Data Science Team. This pivotal role involves leveraging computational and statistical techniques on extensive transcriptomic and genomic datasets, particularly focusing on prostate cancer biology and its clinical implications. The ideal candidate will play a key role in identifying clinically relevant molecular signatures that enhance disease stratification, prognosis, and the development of diagnostics, while effectively communicating findings to both scientific and clinical audiences. This position offers a unique opportunity to bridge the realms of data science, biology, and clinical research through close collaboration with scientists, clinicians, and cross-functional teams to convert complex data into actionable insights.
Full-time|$116K/yr - $170K/yr|Hybrid|Cambridge, MA USA; San Francisco, CA USA
Your Role at Lila SciencesWe are in search of a talented Machine Learning Research Engineer with a focus on LLM post-training. In this pivotal role, you will architect and oversee large-scale training systems, enhance the performance of extensive models, and incorporate state-of-the-art methodologies to boost efficiency and throughput.Key ResponsibilitiesDevelop Ray-based distributed training infrastructure for LLMs and multi-modal models.Implement performance optimizations for large-scale model training, including training and optimization workflows such as SFT, MoE, and long-context scaling.Manage the orchestration of leading-edge and open-source LLMs alongside intricate compute-intensive tools.Create scalable pipelines for data preprocessing and experiment orchestration, utilizing tools for efficient data loading, pipeline parallelism, and optimizer tuning.Establish system-level performance benchmarks and debugging utilities.
About GranicaGranica is an innovative AI research and infrastructure firm dedicated to creating reliable, steerable representations of enterprise data.We establish trust through Crunch, a policy-driven health layer optimizing large tabular datasets for efficiency, reliability, and reversibility. Utilizing this foundation, we are developing Large Tabular Models—systems designed to learn cross-column and relational structures, delivering trustworthy answers and automation with integrated provenance and governance.Our MissionCurrent AI capabilities are hindered not only by model design but also by the inefficiencies of the data that supports it. At scale, each redundant byte, poorly organized dataset, and inefficient data pathway contributes to significant costs, latency, and energy waste.Granica’s mission is to eliminate these inefficiencies. We leverage groundbreaking research in information theory, probabilistic modeling, and distributed systems to craft self-optimizing data infrastructure: systems that continually enhance how information is represented and utilized by AI.Led by Prof. Andrea Montanari from Stanford, Granica’s Research group merges advances in information theory with learning efficiency in large-scale distributed systems. We collectively believe that the next significant leap in AI will originate from innovations in efficient systems, rather than merely larger models.Granica is at the forefront of developing a new category of structured AI models: foundational models designed to learn and reason from the relational, tabular, and structured data that drives the global economy. While many focus on unstructured text or media, we are venturing into the next frontier: systems capable of comprehending and reasoning over structured information.Your ContributionsCreate and prototype algorithms that form the core of structured AI, enhancing representation learning and efficient information modeling for enterprise and tabular data at petabyte scale.Develop adaptive learners merging statistical learning theory with systems optimization at scale, contributing to a new generation of foundational models for structured information.Design architectures that unify symbolic, relational, and neural components, enabling AI systems to reason directly over structured enterprise data.Construct cost models and optimization frameworks that enhance the efficiency of structured learning, both computationally and economically.
About Our TeamAt OpenAI, our mission is to ensure that general-purpose artificial intelligence is developed to benefit all of humanity.The Communications team is dedicated to supporting OpenAI's mission, effectively articulating our technological advancements, core values, and our commitment to building powerful AI safely.About the PositionWe are looking for a seasoned communications professional to join our Platform & Research Communications team. This individual will collaborate closely with the Research Communications Lead and various applied and engineering teams to enhance the public understanding of OpenAI’s research among academics, journalists, policymakers, and the general populace.Your primary responsibility will be to develop and implement external communication strategies related to OpenAI's research initiatives—from foundational model advancements to applied science collaborations—while ensuring accuracy, depth, and alignment with OpenAI’s long-term objectives. We seek a candidate with strong scientific or technical knowledge, exceptional storytelling skills, and a proven ability to navigate complex and high-stakes narratives.In this role, you will work closely with research leadership, individual researchers, policy teams, product teams, and cross-functional communications teams. The position requires both strategic insight and hands-on execution in a dynamic environment where research, product development, and public discourse converge.This role is based in San Francisco, CA, and follows a hybrid work schedule (three days a week in the office). Relocation assistance is available.Your Responsibilities Include:Crafting Research NarrativesCreating clear and credible narratives surrounding OpenAI’s research agenda, breakthroughs, and long-term scientific goals.Translating intricate technical concepts into accessible narratives without oversimplifying or misrepresenting their implications.Defining and reinforcing OpenAI’s perspective on pivotal research topics such as reasoning, alignment, interpretability, and scientific discovery.Leading Media Engagement Focused on ResearchEstablishing and nurturing trusted relationships with leading science, technology, and business journalists.Managing both proactive and reactive media engagements related to research announcements, publications, collaborations, and evolving narratives.Preparing researchers and executives for interviews, briefings, and public engagements.
Full-time|$350K/yr - $475K/yr|On-site|San Francisco
At Thinking Machines Lab, our mission is to empower humanity by advancing collaborative general intelligence. We envision a future where everyone can harness the knowledge and tools necessary to make AI work for their unique objectives.Comprising a team of scientists, engineers, and innovators, we have developed some of the most widely employed AI products, including ChatGPT and Character.ai, as well as open-weight models such as Mistral and popular open-source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.About the RoleAt Thinking Machines, we prioritize a multimodal-first approach. We are seeking new team members to push the boundaries of visual perception and multimodal learning. Our focus is on understanding the interplay between vision and language at scale. We design innovative architectures that integrate pixels and text, create datasets and evaluation methods that assess real-world comprehension, and develop representations that enable models to connect abstract concepts with the physical world. Our aim is to build multimodal systems that seamlessly integrate into real-world applications.Your work will be at the intersection of visual understanding, multimodal reasoning, and large-scale model training. You will contribute to the development of architectures, data, and evaluation tools that teach AI to perceive, comprehend, and collaborate effectively. The ideal candidate is inquisitive about multimodal interfaces, possesses experience in conducting large-scale experiments, and is adept at contributing to complex engineering systems. While we seek individuals with expertise in multimodality, our collaborative environment encourages all new hires to work across modalities as a unified team.This role merges foundational research with practical engineering since we do not differentiate between these roles internally. You will be expected to write high-performance code and analyze technical reports. This position is perfect for someone who enjoys both deep theoretical inquiry and hands-on experimentation and is eager to influence the foundational aspects of AI learning.Note: This is an "evergreen role" that we keep open continuously to express interest in this research area. We receive a high volume of applications, and there may not always be an immediate position that perfectly matches your experience and skills. We encourage you to apply regardless. Applications are reviewed regularly, and we reach out to candidates as new opportunities arise. You are welcome to reapply if your experience increases, but please refrain from applying more than once every six months. Additionally, we may post specific roles for particular project or team needs, where you are also welcome to apply directly in addition to this evergreen role.
About the Role Hex Technologies is at the forefront of the AI revolution, providing an innovative platform that transforms modern Data Science and Data Analytics workflows. As an AI Research Engineer, you will collaborate with product teams to create cutting-edge AI experiences, including the Notebook Agent. Your responsibilities will include conducting experiments, fine-tuning models, deploying AI infrastructure, and developing robust experimentation tools. Your primary focus will be enhancing Hex's context engine and advancing the capabilities of our Notebook Agent, designed for professionals engaged in complex and impactful data tasks. The Notebook Agent serves as a sophisticated data copilot, capable of writing SQL and Python, crafting visually stunning reports, and collaborating with analysts to explore new data inquiries. Your efforts will help data teams within Hex deliver highly accurate and tailored data experiences for their stakeholders, empowering data-driven decision-making across the organization. If you are a passionate builder eager to amplify these capabilities for thousands of users, join us on the leading Data Science platform with unparalleled user context.
Role overview The Principal Research Scientist – Scaling at Databricks leads research projects that advance how the company’s data analytics platform handles large workloads. This San Francisco-based role focuses on designing and improving algorithms that enable efficient large-scale data processing and machine learning. Collaboration is central, with regular work alongside engineering, product, and research teams. What you will do Lead research to develop algorithms that scale for data analytics applications. Work with colleagues across engineering, product, and research to strengthen machine learning capabilities. Use deep expertise to shape the direction and architecture of the Databricks platform. Drive new ideas and solutions that influence the future of data science and analytics at Databricks. Location This role is based in San Francisco, California.
Full-time|On-site|Mountain View, California; San Francisco, California
Join Databricks as a Principal Research Scientist specializing in AI Scaling & Optimization. In this pivotal role, you'll lead groundbreaking research initiatives aimed at enhancing the scalability and efficiency of AI models. Collaborate with cross-functional teams to translate innovative algorithms into practical applications that drive business value.As a key member of our research and development team, you will leverage your expertise to push the boundaries of AI technology, contributing to high-impact projects that shape the future of our platform.
About Cognition Cognition develops applied artificial intelligence, focusing on end-to-end software agents. Notable projects include Devin, an AI software engineer, and Windsurf, an integrated development environment designed for AI-native workflows. The company aims to build AI that works alongside engineers as a true partner, not just a tool. The team is small and highly skilled, bringing together competitive programmers, entrepreneurs, and researchers with backgrounds at organizations like Scale AI, Palantir, Cursor, and Google DeepMind. Role Overview The Mid-Level Researcher in AI Training helps bridge pre-training and post-training phases, directly influencing model performance. This role involves making key decisions about late-stage training that shape the core abilities of Cognition's AI models. Areas of focus include optimizing data mixtures, improving quality, extending context length, and developing scalable synthetic data strategies. Main Responsibilities Data Mix and Quality Optimization: Curate and refine high-quality data mixtures for advanced training. Develop methods for sourcing, filtering, and weighting data to boost model capability and maintain performance. Capability Enhancement: Apply strategies to improve coding, mathematical reasoning, and long-term problem-solving through targeted data and training interventions. Translate research into measurable improvements for AI agents. Synthetic Data Development: Build and evaluate synthetic data pipelines that generate scalable training signals. Examine the strengths and limitations of synthetic data approaches for real-world use. Annealing and Schedule Optimization: Research and fine-tune learning rate schedules, warmup strategies, and resource allocation across training phases. Study how scheduling, data distribution, and model behavior interact. Context Length Extension: Investigate and implement methods to increase context length while preserving performance on shorter contexts. Location This position is based in the San Francisco Bay Area.
