Research Engineer in Performance Reinforcement Learning

Join Anthropic as a Research Engineer on our Cybersecurity Reinforcement Learning team, where you'll contribute to the development of AI systems designed for secure coding, vulnerability remediation, and other defensive cybersecurity initiatives. This role blends research with engineering, allowing you to innovate new methodologies while implementing them in…

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.

About Our Innovative TeamJoin the Synthetic Reinforcement Learning (RL) team at OpenAI, where we pioneer advanced reinforcement learning methodologies that harness synthetic data, simulated environments, and feedback mechanisms to train and evaluate state-of-the-art AI models. Our team is dedicated to exploring innovative approaches like self-play and simulation-driven evaluations, enabling us to enhance model capabilities, generalization, and alignment far beyond the limitations of existing techniques.Your Role and ImpactAs a Research Scientist on the Synthetic RL team, you will create groundbreaking reinforcement learning strategies utilizing synthetic environments and feedback to elevate large-scale AI models. You will collaborate closely with fellow researchers to design rigorous experiments, delve into learning dynamics, and convert research findings into practical training methodologies for our production systems.We seek passionate researchers who thrive on tackling open-ended challenges, appreciate rapid iteration, and aspire for their contributions to significantly influence the training of cutting-edge AI models.This position is located in San Francisco, CA, following a hybrid work model that includes three in-office days per week, along with relocation assistance for new hires.Key ResponsibilitiesConduct research and develop advanced reinforcement learning algorithms.Design and execute experiments to analyze training dynamics and model performance at scale.Collaborate with engineers and fellow researchers to integrate successful methodologies into model training workflows.Ideal Candidate ProfilePossess a robust background in reinforcement learning, machine learning research, or a related discipline.Demonstrate strong engineering skills and proficiency in statistical analysis.Enjoy navigating new problem areas where data, objectives, and evaluations are continuously evolving.Be driven by the desire to see research concepts translate into impactful real-world AI systems.About OpenAIOpenAI is a leading AI research and deployment organization committed to ensuring that general-purpose artificial intelligence benefits all of humanity. We are dedicated to pushing the boundaries of AI capabilities and responsibly deploying these technologies through our innovative products. At OpenAI, we believe that AI must be developed with safety and human considerations at its core, and we value the diverse perspectives, voices, and experiences that contribute to our mission.

Anthropic is looking for a Research Engineer with a focus on Machine Learning, particularly Reinforcement Learning (RL) Velocity. This position involves collaborating with a team to design, build, and refine machine learning systems. Much of the work centers on experimenting with new ideas and advancing AI research. What you will do Work alongside researchers and engineers to develop and optimize machine learning models Explore new methods in reinforcement learning to accelerate progress Contribute to projects that push the boundaries of AI capabilities Location and travel This role offers flexibility to work remotely, with some required travel. Anthropic maintains offices in San Francisco, CA and New York City, NY.

About Our TeamThe Safety Systems organization at OpenAI is dedicated to ensuring that our most advanced AI models are developed and deployed in a responsible manner. We engineer evaluations, safeguards, and safety frameworks to help our models operate as intended in real-world applications.The Preparedness team plays a crucial role within the Safety Systems organization, guided by OpenAI’s Preparedness Framework.While frontier AI models have the potential to benefit humanity, they also introduce significant risks. The Preparedness team is essential in anticipating and preparing for catastrophic risks associated with advanced AI models to ensure that AI fosters positive change.Our mission includes:Monitoring and predicting the evolving capabilities of frontier AI systems, particularly regarding risks that could have catastrophic consequences.Establishing concrete procedures, infrastructure, and partnerships to effectively mitigate these risks and safely manage the development of powerful AI systems.Preparedness integrates capability assessment, evaluations, internal red teaming, and mitigations for frontier models, along with overall coordination on AGI preparedness. This fast-paced and impactful work holds significant importance for both the company and society.About the RoleAs models become increasingly capable—transitioning from tools that assist humans to agents that can autonomously plan, execute, and adapt in the real world—cybersecurity emerges as a critical frontier. The same systems that boost productivity can also lead to increased exploitation.In the role of Researcher focusing on cybersecurity risks, you will be instrumental in designing and implementing a comprehensive mitigation strategy to address severe cyber misuse across OpenAI’s products. This position demands strong technical expertise and extensive collaboration across teams to ensure that safeguards are enforceable, scalable, and effective. You will contribute to the development of robust protections that evolve alongside our products, model capabilities, and attacker behaviors.Key ResponsibilitiesDevelop and implement mitigation strategies for model-enabled cybersecurity threats.Collaborate with cross-functional teams to ensure effective risk management.Continuously assess and iterate on security measures to adapt to new challenges.

Pioneering the Future of Open SuperintelligenceAt Prime Intellect, we are on a mission to construct the open superintelligence ecosystem, encompassing cutting-edge agentic models alongside the infrastructure that empowers individuals to create, train, and deploy them seamlessly. We unify global computational resources into an intuitive control plane, complemented by a comprehensive reinforcement learning post-training suite, including dynamic environments, secure sandboxes, verifiable evaluations, and our innovative asynchronous RL trainer. Our platform empowers researchers, startups, and enterprises to execute end-to-end reinforcement learning at unprecedented scales, allowing for the adaptation of models to diverse tools, workflows, and deployment scenarios.As a Research Engineer within our Reasoning team, you will be instrumental in driving our technological vision, particularly in the area of test-time compute scaling research. If you thrive on harnessing synthetic data to enhance LLM reasoning capabilities, we want to hear from you!Discover more about our exciting project by visiting our insight on decentralized training in the inference-compute paradigm.

Join Anthropic as a Research Engineer focusing on Economic Research. In this role, you will leverage your analytical skills to conduct in-depth economic analysis and contribute to innovative projects aimed at enhancing our understanding of economic models and their implications.

Join Anthropic as an Offensive Security Research Engineer in our Safeguards team, where you will play a critical role in identifying and mitigating security risks. Your expertise will be essential in enhancing our security protocols and ensuring the integrity of our systems. You will collaborate with cross-functional teams to develop innovative solutions that prioritize safety and security.

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.

Join Anthropic as a Senior Software Engineer focused on developing cutting-edge AI-driven cybersecurity products. In this dynamic role, you will collaborate with a passionate team to prototype and build innovative solutions that enhance security applications. Your work will bridge research, product development, and customer engagement, allowing you to contribute significantly to the future of cybersecurity.

Transforming Open Superintelligence InfrastructureAt Prime Intellect, we are pioneering the development of an open superintelligence stack that encompasses everything from cutting-edge agentic models to the infrastructure that empowers anyone to create, train, and deploy them. Our innovative approach aggregates and orchestrates global computing resources into a unified control plane, complemented by an advanced open post-training stack: environments, evaluations, sandboxes, and high-performance training infrastructure for Reinforcement Learning (RL), Supervised Fine-Tuning (SFT), and more. We empower researchers, startups, and enterprises to execute end-to-end reinforcement learning at the forefront of technology, adapting models for real-world tools, workflows, and deployment contexts.We are proud to announce our recent funding achievement of $15 million (totaling $20 million raised) led by Founders Fund, with contributions from Menlo Ventures and notable angel investors including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Chief Scientific Officer of Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI), among many others.Role ImpactThis position is at the forefront of innovative RL and post-training methodologies, bridging the gap between applied agent systems and theoretical research. You will play a crucial role in shaping the alignment, deployment, and practical application of advanced models by:Enhancing Agent Capabilities: Designing and refining next-generation AI agents to address real-world challenges—workflow automation, complex reasoning tasks, and large-scale decision-making.Constructing Reliable Infrastructure: Developing robust systems and frameworks that ensure these agents function reliably, efficiently, and at a massive scale.Bridging Applications & Research: Translating ambiguous objectives into explicit technical requirements that steer product development and research initiatives.Prototyping in Real-World Scenarios: Rapidly designing and deploying agents, evaluations, and harnesses for practical tasks to validate our solutions.Application-Driven Research & InfrastructureInfluencing the direction and features of verifiers, the Environments Hub, training services, and other research platform offerings.Creating high-quality examples, reference implementations, and “recipes” to facilitate easy extensions of the stack.Prototyping agents and evaluation harnesses specifically designed for real-world use cases and external systems.Collaborating with technical end-users (research teams, infrastructure-heavy clients, etc.) to ensure alignment with their needs.

Join Gridware as a Mechanical Research Engineer, where your innovative spirit and engineering expertise will contribute to groundbreaking projects in the energy sector. You will be responsible for conducting research, developing prototypes, and collaborating with a team of skilled engineers to advance our technology solutions.

Join our innovative team at Gridware as an Electrical Research Engineer, where you will play a crucial role in advancing our cutting-edge technology. In this position, you will be responsible for conducting research, developing new electrical systems, and optimizing current technologies to enhance our product offerings.

OpenAI's research infrastructure group creates and maintains the backbone systems for advanced machine learning model training. This team often goes beyond conventional training methods, developing new infrastructure to support novel research at scale. Their work closely connects systems engineering with research progress, making it possible to run experiments that would otherwise be too slow or complex. Role overview The Research Infrastructure Engineer for Training Systems designs and improves the platforms that power large-scale ML training. This role bridges research concepts and the practical systems that make large model training possible. The work has a direct impact on model release timelines and requires building systems that perform reliably in demanding, real-world scenarios. What you will do Build and maintain infrastructure for large-scale model training and experimentation Design APIs and interfaces to simplify complex training workflows and prevent misuse Enhance reliability, debuggability, and performance across training and data pipelines Troubleshoot issues involving Python, PyTorch, distributed systems, GPUs, networking, and storage Create tests, benchmarks, and diagnostic tools to catch regressions early Requirements Interest in building systems that support new training methods, not just optimizing existing ones Strong instincts in systems engineering, especially regarding performance, reliability, and clean abstractions Experience designing APIs and interfaces for researchers and engineers Ability to work across ML research code and production infrastructure Enjoys evidence-based debugging using profiles, traces, logs, tests, and reproducible cases

Join our dynamic team at Cognition as a Research Engineer specializing in Infrastructure. In this role, you will be at the forefront of cutting-edge research, contributing to innovative solutions that shape the future of our infrastructure projects.Your responsibilities will include conducting thorough research, analyzing data, and collaborating with cross-functional teams to implement effective strategies. We are looking for an individual who is passionate about technology and infrastructure, eager to solve complex problems, and ready to drive impactful results.

About Our TeamJoin the Foundations Research team, where we tackle ambitious and innovative projects that could redefine the future of AI. Our mission is to enhance the science behind our training and scaling initiatives, focusing on pioneering frontier models. We are dedicated to advancing data utilization, scaling methodologies, optimization strategies, model architectures, and efficiency enhancements to accelerate our scientific breakthroughs.About the PositionWe are on the lookout for a dynamic technical research lead to spearhead our embeddings-focused retrieval initiatives. You will oversee a talented team of research scientists and engineers committed to developing foundational technologies that enable models to access and utilize the right information precisely when needed. This includes crafting innovative embedding training objectives, architecting scalable vector storage, and implementing adaptive indexing techniques.This pivotal role will contribute to various OpenAI products and internal research initiatives, offering opportunities for scientific publication and significant technical influence.This position is located in San Francisco, CA, where we embrace a hybrid work model, requiring three days in the office weekly, and we provide relocation assistance for new hires.Your ResponsibilitiesLead cutting-edge research on embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning.Supervise a team of researchers and engineers in building an end-to-end infrastructure for training, evaluating, and integrating embeddings into advanced models.Drive advancements in dense, sparse, and hybrid representation techniques, metric learning, and retrieval systems.Work collaboratively with Pretraining, Inference, and other Research teams to seamlessly integrate retrieval throughout the model lifecycle.Contribute to OpenAI's ambitious vision of developing AI systems with robust memory and knowledge access capabilities rooted in learned representations.You Will Excel in This Role If You PossessA proven track record of leading high-performance teams of researchers or engineers within ML infrastructure or foundational research.In-depth technical knowledge in representation learning, embedding models, or vector retrieval systems.Familiarity with transformer-based large language models and their interaction with embedding spaces and objectives.Research experience in areas such as contrastive learning and retrieval-augmented generation.

Join our cutting-edge team at Altos Labs as a Senior Cybersecurity Engineer. In this vital role, you will be responsible for safeguarding our information systems and ensuring the integrity and confidentiality of our data. Your expertise will play a key role in developing and implementing security measures that protect our infrastructure from cyber threats.

Join fuku as an Applied Research Engineer in San Francisco, CA, where you will be at the forefront of AI video data research. As a crucial member of our team, your mission will involve building robust, high-performance frameworks and extensive pipelines to process and decode video data with exceptional accuracy. You will tackle complex research challenges, refine machine learning models and APIs, and deliver comprehensive solutions across computer vision, audio, and text processing domains. This role is designed for engineers who thrive in both research and production environments and are eager to spearhead the evolution of video understanding from research to deployment.

Anthropic is looking for a Research Engineer focused on model evaluations. This position involves research and development to assess and strengthen the performance of AI models. Teams are based in San Francisco and New York City, and the role supports remote work with required travel. Key responsibilities Design and implement evaluations for Anthropic's AI models Collaborate with team members to enhance model performance Contribute to research that pushes the boundaries of AI systems Location Remote-friendly (travel required) San Francisco, CA New York City, NY