AI Research Engineer Jobs

Anthropic

Anthropic is seeking a Research Engineer for its Code RL team, focused on advancing AI models for silicon design. This role involves leveraging chip design expertise to create tasks and signals for AI models, aiming to improve their capabilities in areas like RTL generation, design verification, and physical design optimization. The position sits at the intersection of cutting-edge research and engineering, with a commitment to building high-quality, scalable AI systems.

$500k - $850k

Datadog

Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. DAIR is an industrial research lab motivated by practical challenges in observability and software operation, focusing on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor.

$110k - $140k

Etched is building AI systems that accelerate its own development. As a Research Engineer on the RL Frontiers team, you will train proprietary frontier models to automate kernel development, ASIC engineering, production pipelines, and 3-D hardware operating systems. You will use proprietary simulators and environments to create custom data mixes and post-train models to SOTA performance on the company's hardest engineering tasks. The company is focused on inference and bets on transformer architectures, aiming to capture the entire inference market. Etched is a fully in-person team in San Jose, valuing engineering skills and expecting technical staff to contribute to both engineering and research across disciplines.

From $400k

Lila Sciences is building a talent-dense, high-agency AI safety team focused on identifying and mitigating risks from scientific superintelligence while preserving scientific discovery capabilities. The team's initial focus is to develop and implement a bespoke safety strategy tailored to Lila's specific goals and deployment strategies. This involves technical safety strategy development, broader ecosystem engagement, safety-focused evaluations, safety systems to mitigate risks, and a research agenda exploring long-term needs like overseeing superintelligent scientific systems. We are seeking a materials scientist to map risks across the materials science domain, connecting deep materials expertise with dual-use risk assessment to safeguard scientific AI.

$268k - $384k

AssemblyAI

AssemblyAI is a leading Voice AI company developing foundational speech models that power the next generation of voice applications. We operate at a significant scale, processing millions of hours of audio daily and serving billions of end-user experiences. This is a growth-stage opportunity within a capital-efficient company that offers significant ownership and impact. We foster a flat culture where employees are deeply involved in the details and can drive their work forward without bureaucratic hurdles. If you are passionate about Voice AI and want to solve interesting problems at scale, this is the place for you.

$270k - $310k

Anthropic

Reinforcement learning is crucial for training AI models like Claude to reason, write code, and act autonomously. At scale, RL training involves complex distributed systems running across numerous accelerators and hosts. As an engineer in RL Engineering, you will be responsible for securing this expanding system. This is a hands-on role where you will work directly within the RL codebase and its underlying infrastructure, collaborating with the engineers and researchers who develop and utilize it. The system's rapid evolution, driven by research advancements, requires security solutions that maintain pace without compromising performance or development velocity. We are seeking candidates with expertise in either security engineering for large-scale ML systems or ML systems/research engineering with a strong interest in security.

$320k - $405k

Sygaldry Technologies

Sygaldry Technologies is developing quantum-accelerated AI servers to dramatically speed up AI training and inference. By merging quantum computing with AI, the company aims to accelerate the development of superintelligence and ensure its efficient and affordable operation. Their unique approach involves integrating multiple qubit types into a single, fault-tolerant architecture to achieve the necessary cost, scale, and speed for advanced AI applications. Sygaldry is at the forefront of new discoveries in physics, engineering, and AI, tackling complex challenges with a grounded, optimistic, and rigorous culture. They are seeking individuals passionate about defining the future at the intersection of quantum and AI and driving its global impact.

$125k - $145k

Salesforce AI Research is seeking entrepreneurial Research Interns for Summer 2027 to help build the next generation of Enterprise AI. This is a unique opportunity to work like a founder within Salesforce, exploring high-impact research directions, prototyping cutting-edge AI capabilities, and seeing how ideas are validated with customers and turned into production-ready solutions. Interns will have the freedom to propose and explore new ideas alongside mentors and research scientists, with access to Salesforce's global customer and product ecosystem. The role is ideal for individuals comfortable with ambiguity, bringing energy and focus, and who care as much about customer adoption as technical innovation, offering the pace and ownership of a startup with the reach and resources of Salesforce.

Salary not listed

Anthropic

The Cybersecurity RL team within Horizons is seeking a Research Engineer to advance the capabilities of AI models in secure coding, vulnerability remediation, and defensive cybersecurity. This role combines research and engineering, involving the design and implementation of RL environments, conducting experiments, delivering work into production training runs, and collaborating with cross-functional teams. The ideal candidate will possess domain expertise in cybersecurity and an interest in training safe AI models, potentially coming from backgrounds such as white hat hacking, security engineering, or detection and response.

$500k - $850k

Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Interpretability team focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms. This involves reverse-engineering how trained models work, treating neural networks like biological systems or computer programs to be reverse-engineered. The team's goal is to create a solid scientific foundation for understanding neural networks and making them safe, with a focus on issues like "superposition" and decomposing models into interpretable components. This role supports a team of expert researchers and engineers working on these ambitious safety research goals.

$350k - $500k

Anthropic

The Interpretability team at Anthropic is dedicated to reverse-engineering how trained models work, believing that a mechanistic understanding is crucial for making advanced AI systems safe and steerable. This role focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms, akin to performing "biology" or "neuroscience" on neural networks. The team has made significant progress in understanding issues like "superposition" and decomposing models into interpretable components, with recent work identifying millions of features in production models and developing methods to understand multi-hop reasoning and planning. This research is foundational for building reliable, interpretable, and steerable AI systems and often involves collaboration with other teams at Anthropic to enhance AI safety.

$350k - $850k

NVIDIA is at the forefront of the AI revolution, powering innovations from self-driving cars to intelligent assistants. Join a diverse applied research team focused on building next-generation Conversational AI systems. The team works on novel language models for code and mathematics reasoning, having developed a model that won the latest Kaggle AI MO competition. They also create algorithms to accelerate the training of large models on their GPU cloud and release new models through NeMo, an open-source toolkit for Conversational AI used by numerous companies for applications like customer service and voice assistants. Collaboration extends to research and product teams, as well as leading academic machine learning labs.

Salary not listed

Thinking Machines Lab

Thinking Machines is building AI that extends human will and judgment. We are developing Tinker, a fine-tuning API that empowers researchers and developers to customize frontier AI models. This role focuses on building and enhancing our training systems for Tinker, specifically involving RL systems, numerics, and kernels, to enable users to train models with their own data and algorithms.

$350k - $475k

Genmo is a research lab developing sophisticated video world models to understand, simulate, and interact with the physical world, aiming to unlock the right brain of AGI. We are seeking an exceptional Research Scientist to focus on alignment and post-training techniques for large-scale video generation models. This role is at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate, and safe outputs that align with human preferences and values.

Salary not listed

Prime Intellect

Prime Intellect is building the open superintelligence stack, a platform designed to unify compute, environments, evaluations, and high-performance training for AI labs. Their platform, Lab, supports full-stack systems for post-training at frontier scale, including SFT, RL, tool use, agent workflows, and continuous model improvement. They are focused on creating open-source models for long-horizon tasks like autonomous research and the platform their own research team uses. The company aims to provide AI companies and research teams with the ability to transform their workflows, tools, and data into owned superintelligence.

$150k - $300k

Deepgram

Deepgram is a leading platform for Voice AI, providing real-time APIs for speech-to-text and text-to-speech, enabling developers to build production-grade voice agents at scale. We are seeking researchers who are passionate about solving customer challenges by improving our AI models. This role involves identifying model limitations, designing evaluations, curating data, fine-tuning models, and shipping solutions to production within weeks. The ideal candidate will have an AI-first mindset, be comfortable experimenting with new AI tools and models, and thrive in a fast-paced, evolving environment.

$216k - $338k

Genmo is a research lab focused on developing advanced video world models to understand, simulate, and interact with the physical world, aiming to unlock the right brain of AGI. We are seeking an exceptional Research Scientist to pioneer cutting-edge diffusion models for text-to-video generation. This role involves creating novel architectures and algorithms to transform written descriptions into high-quality, coherent video content, pushing the boundaries of physical intelligence and enabling robots to learn and act in dynamic environments.

Salary not listed

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training for post-training at scale, including SFT, RL, tool use, and agent workflows. They are focused on open-source models trained for long-horizon tasks and the platform used to build them. The company has raised significant funding from prominent investors and is seeking individuals to work at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category.

$150k - $300k

Prime Intellect

Prime Intellect is building an open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training for post-training at scale, including SFT, RL, tool use, agent workflows, and continuous model improvement. They are focused on open-source models for long-horizon tasks and the platform their research team uses. The company has raised significant funding from prominent investors and is looking for individuals passionate about building at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category.

$150k - $300k

Prime Intellect

Prime Intellect is developing an open superintelligence stack, providing infrastructure that AI labs typically build internally to ambitious AI teams. Their platform, Lab, integrates compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for post-training at scale, covering SFT, RL, tool use, agent workflows, and continuous model improvement. They are focused on building open-source frontier AI models trained for long-horizon tasks and the platform their research team uses. The company has secured significant funding from prominent investors and AI leaders, and is seeking individuals passionate about building at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category.

$150k - $300k

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Their work integrates model training, inference algorithms, and serving systems, optimizing all three for reduced cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your solutions against realistic serving workloads, such as long-context and agentic traffic.

Salary not listed

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training for post-training at frontier scale. They are developing open-source models for long-horizon tasks and the platform their research team uses. The company has raised $150M from prominent investors and AI leaders. They are seeking individuals passionate about building at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category. This role focuses on building the data foundation for Prime Intellect's next generation of open models. You will identify and process valuable data sources, transforming them into training-ready corpora. Your work will directly influence both broad pretraining efforts and the development of specific capabilities like reasoning, coding, and long-context learning. You will collaborate closely with researchers to test and refine data strategies, ensuring the data effectively improves model performance.

$150k - $350k

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Our work spans model training, inference algorithms, and serving systems, aiming to reduce generation cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your ideas against realistic serving workloads, such as long-context and agentic traffic. Projects are designed to address key research questions in speculative decoding, leading to faster generation on frontier models, drafters that adapt to changing workloads, and robust evaluation under real traffic.

Salary not listed

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for post-training at frontier scale. We are developing open-source models trained end-to-end for long-horizon tasks like autonomous research, alongside the full-stack platform our research team utilizes. We are seeking individuals passionate about building at the intersection of frontier research, real infrastructure, and go-to-market for a nascent category.

$150k - $350k