Principal Research Scientist – Scaling

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.

Join Scale Labs as a Research Scientist — Agent RobustnessScale is the premier partner for data and evaluation within the forefront of AI innovation, playing a crucial role in understanding and safeguarding AI models and systems. Building on our extensive expertise, Scale Labs has initiated a dedicated team focused on policy research, aiming to connect AI research with global policymakers to facilitate informed, scientifically grounded decisions regarding AI risks and capabilities.Our research addresses complex challenges in agent robustness, AI control protocols, and AI risk evaluations, empowering governments, industries, and the public to comprehend and mitigate AI risks while promoting AI adoption. This team collaborates across various sectors, including industry, public services, and academia, and regularly disseminates our findings. We are actively inviting skilled researchers to contribute to this vision.As a Research Scientist specializing in Agent Robustness, you will tackle foundational challenges in creating AI agents that are both safe and aligned with human values. Your responsibilities may include:Investigating the science behind AI agent capabilities, focusing on safety, risk factors, and benchmarking methodologies.Designing and building testing harnesses to evaluate AI agents' tendencies to engage in harmful actions under user pressure or environmental manipulation.Creating exploits and mitigations for new failure modes that emerge as AI agents gain capabilities such as coding, web browsing, and computer usage.Characterizing and developing mitigations for potential failure modes or broader risks involving multiple interacting AI agents.

At Scale AI, we collaborate with leading AI laboratories to supply high-quality data and foster advancements in Generative AI research. We seek innovative Research Scientists and Research Engineers with a strong focus on post-training techniques for Large Language Models (LLMs), including Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and reward modeling. This position emphasizes optimizing data curation and evaluation processes to boost LLM performance across text and multimodal formats. In this pivotal role, you will pioneer new methods to enhance the alignment and generalization of extensive generative models. You will work closely with fellow researchers and engineers to establish best practices in data-driven AI development. Additionally, you will collaborate with top foundation model labs, providing critical technical and strategic insights for the evolution of next-generation generative AI models.

Join Scale Labs as a Research Scientist – AI Controls and MonitoringScale AI is at the forefront of data solutions for pioneering AI enterprises, playing a crucial role in understanding and protecting AI models and systems. Our new team within Scale Labs is dedicated to policy research, bridging the divide between AI advancements and global policymakers to make informed and scientific decisions regarding AI risks and capabilities.We tackle complex challenges in agent robustness, AI control mechanisms, and risk evaluations, assisting governments, industries, and the public in understanding and mitigating AI risks while fostering AI adoption. Our collaborative efforts involve partnerships across various sectors, including industry, public entities, and academia, and we regularly share our findings with the community. We are looking for passionate researchers to help us fulfill this vision.As a Research Scientist specializing in AI Controls and Monitoring, you will develop methodologies, systems, and experiments to ensure advanced AI models and agents stay aligned with their intended goals, even in critical or adversarial situations. Your responsibilities may include:Creating monitoring strategies and observability techniques to track AI behavior in real-time, identifying and flagging deviations, emergent capabilities, or anomalous outputs;Investigating layered control mechanisms, including fail-safes, oversight protocols, and intervention strategies to redirect AI systems when risks arise;Designing red-team simulations to uncover vulnerabilities in oversight and control frameworks, and implementing measures to address identified gaps;Collaborating with policymakers, engineers, and researchers to establish standards and benchmarks for AI monitoring and escalation.

Join Scale AI as a Research Scientist — Frontier Risk EvaluationsAt Scale AI, we are at the forefront of data and evaluation services for pioneering AI technologies. Our mission is to ensure the safe and effective deployment of AI systems by bridging the gap between advanced AI research and global policy frameworks. With the launch of Scale Labs, we are assembling a dedicated team focused on policy research to empower governments and industry leaders with scientific insights regarding AI risks and functionalities.This team addresses complex challenges in agent robustness, AI control mechanisms, and risk assessments to facilitate a comprehensive understanding of AI risks, while promoting its responsible adoption across various sectors. We are eager to welcome skilled researchers who are passionate about shaping the future of AI.As a Research Scientist specializing in Frontier Risk Evaluations, you will be responsible for designing evaluation metrics, harnesses, and datasets to assess the risks associated with cutting-edge AI systems. Your role may involve:Developing harnesses to evaluate AI models for potential security vulnerabilities and other high-risk behaviors.Collaborating with government entities and research labs to design evaluations that mitigate risks posed by advanced AI technologies.Publishing evaluation methodologies and drafting technical reports aimed at informing policymakers.

About Scale AI At Scale AI, we are committed to propelling the advancement of AI technologies. For over eight years, we have been a pioneer in the AI data sector, supporting groundbreaking innovations in areas such as generative AI, defense solutions, and autonomous driving. Following our recent Series F funding round, we are enhancing access to premium data to accelerate the journey towards Artificial General Intelligence (AGI). Building on our legacy of model evaluation for both enterprise and governmental clients, we are expanding our capabilities to establish new benchmarks for evaluations in both public and private domains. About This Role This position is at the leading edge of AI research and practical implementation, concentrating on reasoning within large language models (LLMs). The successful candidate will investigate critical data types vital for evolving LLM-based agents, including browser and software engineering agents. You will significantly influence Scale’s data strategy by pinpointing optimal data sources and methodologies to enhance LLM reasoning. To excel in this role, you will require a profound understanding of LLMs, planning algorithms, and fresh approaches to agentic reasoning, alongside inventive solutions to challenges in data generation, model interaction, and evaluation. Your contributions will lead to transformative research on language model reasoning, facilitate collaboration with external researchers, and engage closely with engineering teams to translate cutting-edge advancements into scalable, real-world applications.

At Scale AI, we are at the forefront of artificial intelligence, driving innovation through our advanced data, infrastructure, and tooling that empower the most sophisticated models worldwide. Our teams thrive at the intersection of pioneering research, extensive engineering, and practical deployment, collaborating with leading labs, enterprises, and government entities to explore the vast potential of Generative AI. As AI technology evolves from static models to dynamic, intelligent systems, Scale AI is dedicated to establishing the essential research foundations, evaluation methodologies, and reinforcement learning infrastructure that will shape this transformative era. Join our high-impact research organization, where you will contribute to advancing large language models, post-training evaluation, and agent-based reinforcement learning environments, influencing the future of AI development and implementation. As the Research Scientist Manager, you will spearhead a distinguished team of research scientists and engineers, define the strategic research roadmap, and oversee projects from initial prototyping to final deployment. You will excel in a fast-paced environment, harmonizing deep technical leadership with effective people management, visionary goal setting, and successful delivery.

Join ASM – Where Innovation Meets Collaboration!With over 55 years of pioneering technology, ASM stands at the forefront of innovation, shaping the future of advanced semiconductor devices. Our diverse team of more than 4,500 professionals from 70 nationalities drives advancements in key trends such as 5G, cloud computing, AI, and autonomous driving. We pride ourselves on our commitment to diversity, inclusion, and sustainability, striving to make a positive impact on the world. Our comprehensive development programs are designed to foster your growth, enabling you to push the boundaries of innovation. Position: Senior Principal Engineer, Systems (Plasma & Multi-Scale Simulation Scientist)The Simulation and Modeling Hub is looking for a Senior Plasma & Multi-Scale Simulation Scientist to enhance our plasma modeling capabilities. This pivotal role involves integrating plasma physics, surface chemistry, and feature-scale behavior to develop predictive, physics-based simulation workflows that support advanced semiconductor processes including PEALD, PECVD, ALE, and RIE.

About Scale AI At Scale AI, we are dedicated to propelling the advancement of AI applications. Over the past eight years, we have established ourselves as the premier AI data foundry, supporting groundbreaking innovations in fields such as generative AI, defense technologies, and autonomous vehicles. Following our recent Series F funding round, we are intensifying our efforts to harness frontier data, paving the way toward achieving Artificial General Intelligence (AGI). Our work with enterprise clients and governments has enhanced our model evaluation capabilities, allowing us to expand our offerings for both public and private evaluations. About the ACE Team The Agent Capabilities & Environments (ACE) team, a vital part of Scale’s Research organization, unites customer-focused Researchers and Applied AI Engineers. Our primary mission is to conduct research on agent environments and reinforcement learning reward signals, benchmark autonomous agent performance in real-world contexts, and develop robust data programs aimed at enhancing the capabilities of Large Language Models (LLMs). We are committed to creating foundational tools and frameworks for evaluating models as agents, focusing on autonomous agents that interact dynamically with a wide range of external environments, including code repositories and GUI interfaces. About This Role This position sits at the cutting edge of AI research and its practical applications, concentrating on the data types necessary for the development of state-of-the-art agents, including browser and software engineering agents. The ideal candidate will investigate the data landscape required to propel intelligent and adaptable AI agents, steering the data strategy at Scale to foster innovation. This role demands not only expertise in LLM agents and planning algorithms but also creative problem-solving skills to tackle novel challenges pertaining to data, interaction, and evaluation. You will contribute to influential research publications on agents, collaborate with customer researchers, and partner with the engineering team to transform these advancements into scalable real-world solutions.

Join OpenAI as a Research Scientist and explore cutting-edge machine learning innovations. In this role, you will be at the forefront of developing groundbreaking techniques while advancing our team's research initiatives. Collaborate with talented peers across various teams to discover transformative ideas that scale effectively. We seek individuals who are passionate about pushing the boundaries of AI and want to contribute to our unified research vision.

Join worldlabs as a Research Engineer focused on scaling multimodal data. In this dynamic role, you will leverage cutting-edge technologies and methodologies to enhance data processing capabilities. You will be responsible for developing innovative solutions that integrate various data types and drive impactful research outcomes.

Merge Labs is an innovative research facility dedicated to merging biological sciences and artificial intelligence to enhance human capability, autonomy, and experience. Our mission is to pioneer revolutionary methodologies in brain-computer interfaces that facilitate high-bandwidth interactions with the brain, seamlessly integrate advanced AI, and maintain safety and accessibility for all users.About the TeamAt Merge, we are addressing some of the most ambitious challenges in molecular engineering, synthetic biology, and neuroscience. Our Research Platform Team is responsible for creating the experimental frameworks necessary to tackle these challenges with exceptional speed and precision. The tools and methodologies developed by our team significantly enhance molecular assembly, protein expression, mammalian cell culture, advanced microscopy, sequencing, and unique custom techniques. We collaborate with program teams to establish and optimize these capabilities, implement automation where beneficial, and integrate with our data science and machine learning pipelines, continuously pushing the boundaries of throughput and innovation.About the RoleAs a Platform Scientist, you will be instrumental in developing high-efficiency and high-throughput experimental pipelines that accelerate research initiatives. You will work closely with program leads, project scientists, data scientists, and engineers, leading your work and potentially recruiting additional team members as necessary.Key Responsibilities:Collaborate with program leads and scientists to identify critical experimental requirements and workflows.Develop processes to facilitate high-throughput and/or high-efficiency experiments, including reagent production and analysis.Scope, procure, construct, program, and validate instruments to support experimental workflows.Ensure the quality, reliability, and integrity of data generated from automated pipelines, including defining and implementing suitable quality control checkpoints.Work alongside data science and machine learning engineers to incorporate metadata tracking, computational design, and analysis into experimental pipelines.Partner with electrical, mechanical, and software engineers to create custom setups.Innovate and validate concepts to enhance experimental throughput.

OverviewBecome an integral part of our dynamic R&D team dedicated to developing fully automated research systems that push the boundaries of AI. Zochi has achieved a milestone by publishing the first entirely AI-generated A* conference paper. Locus has set a new industry standard as the first AI system to surpass human experts in AI R&D.Key ResponsibilitiesConceptualize and develop innovative architectures for automated research.Work collaboratively within a specialized team of researchers addressing cutting-edge challenges in long-horizon agentic capabilities, post-training for open-ended objectives, and environment crafting.Document and publish key internal findings alongside success stories from external collaborations.QualificationsPhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline. Outstanding candidates with significant research contributions are encouraged to apply, regardless of formal qualifications.Demonstrated history of impactful AI/ML research contributions in academic or corporate environments.Expertise in developing long-horizon, multi-agent systems and/or model post-training, especially in scientific domains or for open-ended discovery objectives.A strong passion for advancing problem-solving processes and scientific discovery, thriving in high-autonomy roles and environments.Our CultureCompetitive compensation and equity options.Unlimited Paid Time Off (PTO), emphasizing team collaboration and a community-focused workplace.Opportunities for conference participation and engagement in community initiatives.Empowered roles with high levels of responsibility.#1: We are a small, passionate team of leading investors, researchers, and industry experts committed to the mission of accelerating discovery. Join us.

About the TeamJoin the innovative Post-Training team at OpenAI, where we focus on refining and elevating pre-trained models for deployment in ChatGPT, our API, and future products. Collaborating closely with various research and product teams, we conduct crucial research that prepares our models for real-world deployment to millions of users, ensuring they are safe, efficient, and reliable.About the RoleAs a Research Engineer / Scientist, you will spearhead the research and development of enhancements to our models. Our work intersects reinforcement learning and product development, aiming to create cutting-edge solutions.We seek passionate individuals with robust machine learning engineering skills and research experience, particularly with innovative and powerful models. The ideal candidate will be driven by a commitment to product-oriented research.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 new employees.In this role, you will:Lead and execute a research agenda aimed at enhancing model capabilities and performance.Work collaboratively with research and product teams to empower customers to optimize their models.Develop robust evaluation frameworks to monitor and assess modeling advancements.Design, implement, test, and debug code across our research stack.You may excel in this role if you:Possess a deep understanding of machine learning and its applications.Have experience with relevant models and methodologies for evaluating model improvements.Are adept at navigating large ML codebases for debugging purposes.Thrive in a fast-paced and technically intricate environment.About OpenAIOpenAI is a pioneering AI research and deployment organization dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We are committed to pushing the boundaries of AI capabilities while prioritizing safety and human-centric values in our products. Our mission is to embrace diverse perspectives, voices, and experiences that represent the full spectrum of humanity, as we strive for a future where AI is a powerful ally for everyone.

About Our TeamJoin the forefront of AI innovation with the RL and Reasoning team at OpenAI. Our team is dedicated to advancing reinforcement learning research and has pioneered transformative projects, including o1 and o3. We are committed to pushing the limits of generative models while ensuring their scalable deployment.About the RoleAs a Research Engineer/Research Scientist at OpenAI, you will play a pivotal role in enhancing AI alignment and capabilities through state-of-the-art reinforcement learning techniques. Your contributions will be essential in training intelligent, aligned, and versatile agents that power various AI models.We seek individuals with a solid foundation in reinforcement learning research, agile coding skills, and a passion for rapid iteration.This position is located in San Francisco, CA, and follows a hybrid work model of three days in the office per week. We also provide relocation assistance for new hires.You may excel in this role if:You are enthusiastic about being at the cutting edge of RL and language model research.You take initiative, owning ideas and driving them to fruition.You value principled methodologies, conducting simple experiments in controlled environments to draw trustworthy conclusions.You thrive in a fast-paced, complex technical environment where rapid iteration is essential.You are adept at navigating extensive ML codebases to troubleshoot and enhance them.You possess a profound understanding of machine learning and its applications.About OpenAIOpenAI is a pioneering AI research and deployment organization committed to ensuring that general-purpose artificial intelligence serves the greater good for humanity. We strive to push the boundaries of AI system capabilities while prioritizing safe deployment through our innovative products. We recognize AI as a powerful tool that must be developed with safety and human-centric principles, embracing diverse perspectives to reflect the full spectrum of humanity.We are proud to be an equal opportunity employer, welcoming applicants from all backgrounds without discrimination based on race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or any other legally protected characteristic.

As a premier data and evaluation partner for cutting-edge AI firms, Scale AI is committed to enhancing the evaluation and benchmarking of large language models (LLMs). We are developing industry-leading LLM evaluations that set new benchmarks for model performance assessment. Our mission is to create rigorous, scalable, and equitable evaluation methodologies that propel the next evolution of AI capabilities.Our Research teams collaborate with top AI laboratories to provide high-quality data and expedite advancements in Generative AI research. As the Tech Lead/Manager of the LLM Evaluations Research team, you will guide a skilled team of research scientists and engineers dedicated to crafting and applying innovative evaluation methodologies, metrics, and benchmarks that assess the strengths and weaknesses of our advanced LLMs. This pivotal role involves designing and executing a strategic roadmap that establishes best practices in data-driven AI development, thus accelerating the development of the next generation of generative AI models in collaboration with leading foundational model labs.

Join our dynamic team at Amgen as a Principal Scientist - Biotransformation in San Francisco. In this pivotal role, you will lead innovative research focusing on biotransformation processes, contributing to the development of cutting-edge therapeutics. Your expertise will drive scientific advancements and support our mission to improve the lives of patients worldwide.

Join Our Team as a Research ScientistAt Parallel, we are at the forefront of web infrastructure innovation, enabling businesses across sectors such as sales, marketing, insurance, and technology to harness the power of AI. Our state-of-the-art products empower users to develop superior AI agents with seamless and flexible access to the web.With significant backing of $130 million from prominent investors like Kleiner Perkins, Index Ventures, and Spark Capital, we are dedicated to redefining the web for artificial intelligence. As we expand, we're assembling a top-tier team of engineers, designers, marketers, sales experts, researchers, and operational specialists committed to our vision.Your Role: As a Research Scientist, you will tackle the challenge of training and scaling models designed to enhance web indexing capabilities.About You: You possess a profound understanding of contemporary models and training methodologies. You enjoy engaging in discussions about the convergence of search, recommendations, and transformer models, and are passionate about translating your research into impactful products and systems utilized by millions.

Join Merge Labs, a pioneering research facility dedicated to merging biological and artificial intelligence to enhance human capabilities, agency, and experience. We aim to achieve this by crafting innovative brain-computer interfaces that communicate with the brain at high bandwidth, seamlessly integrate with cutting-edge AI, and prioritize safety and accessibility for all users.About the Team:At Merge Labs, we are on a mission to revolutionize brain-computer interfaces by leveraging advancements in synthetic biology, neuroscience, AI, and non-invasive imaging technologies. Our cross-functional data science team is situated at the convergence of computational modeling, neuroscience, and biomolecular engineering. This collaborative unit works closely with wet-lab scientists, automation specialists, and data engineers to develop machine learning frameworks that facilitate rapid molecule discovery and device enhancement.About the Role:We are seeking a talented Senior / Principal ML Scientist to architect and scale Bayesian optimization and reinforcement learning frameworks that guide molecular engineering initiatives through iterative design-build-test-learn (DBTL) cycles. You will start with a fresh approach to construct the company's closed-loop optimization infrastructure, establishing the data and modeling foundations that link experiments with these ML frameworks. Over time, you will transition prototypes into operational pipelines, significantly enhancing experimental throughput and discovery success across various biomolecular and neuroengineering sectors.Key Responsibilities:Develop the scientific and engineering framework for active learning and closed-loop optimization, encompassing data ingestion, ML modeling, and library design.Collaborate with wet-lab scientists to establish feasible optimization objectives while incorporating domain-specific priors and constraints.Create prototypes for representation learning and acquisition strategies utilizing both internal and public datasets; benchmark and validate the performance of models.Integrate machine learning models with experimental data streams, making them accessible to non-domain experts for broader utilization.Extend machine learning frameworks to accommodate multi-objective or constrained optimization challenges.Stay abreast of the latest advancements in Bayesian optimization, active learning, and reinforcement learning, and prototype innovative algorithms to enhance the company's capabilities.

Zyphra is a pioneering artificial intelligence firm located in the vibrant city of San Francisco, California.About the Role:We are seeking a passionate Research Scientist to join our dynamic Agency and Reasoning Team at Zyphra. In this role, you will conduct cutting-edge research in reinforcement learning, post-training methodologies, and human preference learning. Your innovative ideas will be instrumental in shaping our next-generation language models, enabling their application on a large scale.What We Desire:A strong sense of research intuition and tasteCapability to navigate a research project from initial concept to execution and documentationProficiency in implementation and prototypingA quick thinker who can rapidly transform ideas into experimental frameworksAbility to collaborate effectively in a fast-paced research environmentAn insatiable curiosity and enthusiasm for the study of intelligence.Qualifications:Proven experience and skill in reinforcement learning, particularly in the context of language model reasoning or classical RL tasksFamiliarity with language-model-supervised fine-tuning and preference-learning techniques, such as DPO and simPO.Experience with methods for context-length extensionStrong intuitive understanding of model behaviors, with the ability to refine them through iterative fine-tuningInterest in engaging deeply with data and dedicating time to data engineering and synthetic data generationA postgraduate degree in a scientific discipline (Computer Science, Electrical Engineering, Mathematics, Physics)Published research in reputable machine learning venuesExpertise in PyTorch and PythonEagerness and aptitude for rapidly acquiring new knowledge and implementing innovative conceptsExceptional communication and teamwork abilities, capable of contributing to both research and large-scale engineering effortsWhy Join Zyphra?We champion creative and unconventional ideas and are prepared to invest significantly in innovative concepts.Our culture fosters collaboration, curiosity, and intellectual growth.