AI Research Engineer Jobs

Turing

Turing is seeking exceptional Research Scientists to join our STEM research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science. We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them.

$250k - $350k

Turing

Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for leading AI labs and enterprises. We create RL environments to evaluate and improve models on complex, long-range, multi-step workflows across high-value domains. We are seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

$250k - $350k

Turing

Turing is seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

$250k - $350k

Turing

Turing is seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

$250k - $350k

Turing

Turing is seeking exceptional AI Research Scientists to join our STEM research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science. We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them.

$150k - $300k

Turing

Turing is seeking a Research Engineer to contribute to the development of frontier-quality datasets, reinforcement learning environments, and evaluations for state-of-the-art models. This role involves close collaboration with client researchers and engineers, translating research goals into technical proposals and data specifications, and overseeing technical execution. You will be responsible for building quality and verification systems to ensure deliverables meet high standards for correctness, realism, diversity, and measurable model lift. The work is bespoke, focusing on a single frontier lab client to build deep context and relationships, with flexibility to support other accounts. Success is measured by both turnaround time and quality. This position is ideal for individuals experienced in building and improving deep learning systems, with a strong emphasis on data quality, curation, denoising, synthetic data generation, and rigorous evaluation.

Salary not listed

Turing

Turing is seeking a Research Engineer to contribute to the development of cutting-edge AI datasets, reinforcement learning environments, and evaluations for leading AI labs and enterprise clients. This is a hands-on, research-focused technical leadership role where you will collaborate with customer researchers and engineers to define data and environment specifications based on their model and post-training objectives. You will be responsible for driving the production of high-quality data that meets stringent standards for correctness, realism, diversity, difficulty, and measurable model improvement. The role is ideal for individuals with approximately 4-5 years of experience in building and refining deep learning systems, particularly those where data quality, curation, denoising, synthetic data generation, and rigorous evaluation are critical for success. You will operate within one or more specialized capability areas, including coding and software engineering agents, RL environments, multimodal data and reasoning, STEM reasoning, and modern embodied AI agents.

Salary not listed

This internship is focused on ML research mixed with applied ML and software engineering, specifically around trust and safety in LLMs. Topics include prompt injections, safety alignment and guardrails, privacy and confidentiality, and interpretability. Other topics closer aligned with the student's research may also be considered.

Salary not listed

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI training labs. As a Senior Research Infrastructure Engineer, you will accelerate research on training and evaluating frontier AI agents by building the software and infrastructure that enables researchers to iterate on environments, collect trajectories, and evaluate model behavior. You will collaborate closely with research engineers to understand their needs, identify bottlenecks, and transform research code into robust, reusable systems, owning the tools, pipelines, and execution infrastructure that support their exploration and scaling of promising approaches.

$175k - $260k

Sieve

Sieve is seeking its first Robotics Researcher to lead the training and evaluation of world-action models (WAMs) and 3D perception systems. This role focuses on understanding how data shapes robot capabilities, connecting data curation and labeling to measurable gains in robot learning. You will manage projects from inception to completion, identifying model shortcomings, determining data needs, setting up experiments, and testing results on unseen tasks and environments. A significant portion of this work involves 3D, transforming raw multimodal and egocentric video into actionable data for robot learning by incorporating geometry, pose, and action. Simulation will be used as a tool for evaluation and augmentation when beneficial, but not as the primary focus.

Salary not listed

We are seeking a hardworking intern with expertise in Reinforcement Learning and Multi-Modal World Simulation Models to advance ML-centric autonomous driving and Physical AI solutions. The role focuses on model-centric RL, understanding world simulation models, and applying state-of-the-art algorithms to real-world applications, enabling vehicles to interpret, anticipate, and respond effectively in dynamic environments. This is an opportunity to contribute to the future of intelligent driving, where innovation drives real-world impact. If you are passionate about building simulation technologies and systems that learn, adapt, and think, we encourage you to apply. Join a team where your contributions are vital to accelerating autonomous vehicle growth with advanced solutions.

Salary not listed

OpenAI

OpenAI's Safety Research organization is seeking a senior researcher to lead technical work on misalignment monitoring for frontier AI systems. This role involves developing methods to evaluate AI monitors, understanding their limitations, and improving our ability to reliably detect and stop concerning model behavior. You will set research priorities, design rigorous evaluations, investigate monitoring failures, and develop approaches for stress-testing and improving monitoring systems, with a key focus on understanding monitor limitations as models evolve. The position combines research leadership with hands-on technical execution, translating research findings into practical improvements for OpenAI's safety systems.

$380k - $500k

Outset is building AI systems, referred to as digital twins, that represent specific real people and can respond to research questions as those individuals would. These systems are used by global brands to gain deeper qualitative insights about their users at unprecedented speed and scale. The Digital Twins Team focuses on measuring and improving the faithfulness of these AI systems in reproducing human responses and behavior. The Research Scientist will work closely with the Head Scientist to define research questions, design studies, establish measurement criteria, interpret findings, and contribute to internal decision-making and potential academic publications. This role requires a strong background in computational social science, data science, survey methodology, human-computation interaction, and experiment design.

$200k - $240k

Reflection ai

Reflection is a research lab dedicated to making intelligence open and accessible for everyone. We build open models that empower individuals to control their intelligence and shape the future of AI. This role focuses on the foundational aspects of AI development, specifically in pre-training data, contributing to the creation of open foundational models. You will be part of a talented team, helping to define the company's future and the future of open AI.

Salary not listed

Scale AI

Scale's Machine Learning Research team is at the forefront of AI development, building the foundation for next-generation AI systems. We push the boundaries of frontier models, focusing on safety, reliability, and alignment. Our work encompasses generative AI, reinforcement learning, advanced post-training methods, scalable oversight, synthetic data, red teaming, and evaluation science. We are developing a large-scale hybrid human-machine system to power ML pipelines for numerous industry-leading customers, supporting complex and advanced AI use cases. As an intern, you will contribute to impactful production ML applications and cutting-edge research, guided by world-class researchers and collaborating with leading teams across industry and academia. Interns are expected to deliver real, published, or shipped work.

$120k - $150k

Abundant

Abundant is building the NVIDIA of training data, recognizing the critical need for scaling data as AI models advance beyond supervised learning to reinforcement learning and learning from experience. Our founding team brings deep expertise from leading AI organizations, with a proven track record in deploying large-scale deep learning models, training state-of-the-art self-driving models, and managing massive data pipelines. We are at the forefront of innovation, addressing the scarcity of training data by advancing simulation, synthetic data generation, and learning from experience, which are essential for achieving AGI, ASI, and physical intelligence. We partner with top AI labs and enterprises to provide the data necessary for models to move from general knowledge to domain expertise and from chatbots to agents.

$168k - $168k

Outset is building AI-powered user interviews, creating digital twins that represent specific real people and respond to research questions as those individuals would. The Digital Twins Team focuses on measuring and improving how faithfully these AI systems reproduce human responses and behavior. As a Research Engineer, you will report to the Head Scientist and be responsible for building and maintaining the systems that enable the team's scientists to conduct their studies correctly, reproducibly, and at scale. Your role involves ensuring experiments execute as designed, results are reproducible, and research code stays aligned with the shipped product, supporting scientists in a computational research setting with hands-on experience in LLM-based systems.

$200k - $240k

Scale AI

Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.

$290k - $363k

Scale AI

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

$302k - $378k

Scale AI

Scale Labs is seeking a Research Scientist focused on Safety Post-Training to develop and apply methods for making frontier AI systems safer and more understandable. This role involves designing and executing post-training pipelines to analyze how training choices impact model safety, robustness, and alignment. You will also develop evaluations informed by interpretability techniques to uncover the reasons behind undesirable model behaviors and use these insights to guide targeted safety mitigations. A key aspect of this position is collaborating with policymakers, engineers, and other researchers to translate findings into actionable safety standards, benchmarks, and best practices.

$216k - $270k

Scale AI

Scale Labs is launching a new team focused on policy research to bridge the gap between AI research and global policymakers, enabling informed, scientific decisions about AI risks and capabilities. This team tackles complex problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. The Research Scientist, AI Controls and Monitoring will design methods, systems, and experiments to ensure advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments.

$216k - $270k

Scale AI

Scale works with leading AI labs to accelerate GenAI research by providing high-quality data. This role focuses on optimizing data curation and evaluation to enhance LLM capabilities in text and multimodal modalities. You will develop novel methods to improve the alignment and generalization of large-scale generative models, collaborate with researchers and engineers on best practices in data-driven AI development, and partner with foundation model labs to provide technical and strategic input on next-generation generative AI models.

$166k - $207k

OpenAI

The Foundations Research team is focused on high-impact, forward-looking AI research, particularly for future frontier models. Within this team, the Search group is developing agentic search capabilities by co-designing model-system interfaces with the core search stack, including serving, indexing, and retrieval. We build and research large-scale systems to transform and index vast amounts of data, enabling AI models to effectively find and reason over information. This role involves researching and developing methods for extracting and utilizing semi-structured knowledge graphs from heterogeneous web content. The core objective is to make this information more accessible and useful for AI models, addressing key questions about the optimal structure for information retrieval, scalable extraction techniques, and how to measure and improve model reasoning capabilities. You will collaborate across research, data, and systems to advance how knowledge is extracted, organized, and retrieved, with potential for scientific publication and impact across OpenAI products.

$380k - $850k

Lila Sciences is building Scientific Superintelligence™ to accelerate discovery across medicine, materials, and energy. We are seeking a talented individual contributor to join our AI safety team, focusing on identifying and mitigating risks from scientific superintelligence. This role involves developing and implementing a bespoke safety strategy tailored to Lila's specific goals and deployment strategies. You will work with domain scientists, risk researchers, evaluators, and engineering teams to translate risk findings and policy requirements into effective interventions, spanning research and implementation. The work includes developing approaches, testing their limits, and integrating reliable safeguards into our systems.

$224k - $336k