AI Engineering Jobs with Visa Sponsorship

Photoroom is seeking a Product ML Engineer to join one of its product experience teams. This role focuses on owning the machine learning aspects of short, high-impact projects with clear product outcomes. You will be responsible for the entire ML project lifecycle, from problem framing and approach selection to shipping, measuring, and iterating on features in production. The emphasis is on pragmatic, fast-paced development and delivering customer value, rather than pure research. You will work closely with product teams, leverage shared ML infrastructure, and stay connected to user feedback to drive product improvements.

Salary not listed

Anthropic

Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist who combines deep chemistry knowledge with machine learning expertise to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be a computational chemist who knows reactions, synthesis, and medicinal chemistry in depth and has hands-on experience training and evaluating machine learning models. Above all, you'll build the reinforcement learning environments, datasets, and evaluations that teach Claude chemistry. Working alongside our bench chemists and AI researchers, you'll turn real chemistry problems and experimental data into training tasks and measure whether the models get better at them.

$300k - $320k

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

Anthropic

As a TPU Kernel Engineer, you will be responsible for identifying and addressing performance issues across various ML systems, including research, training, and inference. A significant part of this role involves designing and optimizing kernels specifically for the TPU. You will also provide crucial feedback to researchers regarding how model changes affect performance. The ideal candidate will have a proven history of solving large-scale systems problems and demonstrating expertise in low-level optimization.

$280k - $850k

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

Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. This role sits at the center of our datasets team, which owns the driving data our AI Driver learns from, covering ingestion, annotation, retrieval, and data quality. As our data grows towards exabyte scale, deciding what data to keep and where is a major lever on both model quality and cost. You will shape the data that model engineers train on across the company, defining our dataset content strategy and steering data selection based on current model engineering needs.

$390k - $460k

Wayve is building the AI platform for autonomous driving, enabling vehicles to learn directly from real-world experience and adapt at scale. This role is on the Vehicle Generalization Team, focused on making Wayve's core autonomy generalize across a wide range of vehicle platforms. You will work on pre- and post-training methods to improve AI model generalization, specifically addressing how models perform with changes in perception and embodiment across different vehicles. Your work will directly impact production programs with major OEMs.

$370k - $420k

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

Anthropic

Anthropic's Safeguards team is looking for a Red Team Engineer to ensure the safety of their AI systems and products. This role involves taking an adversarial approach to find vulnerabilities before malicious actors can exploit them. The work covers technical infrastructure weaknesses and emergent risks from advanced AI capabilities, focusing on broader safety implications and novel abuses unique to AI systems. You will simulate sophisticated threat actors, investigate potential abuse like account manipulation and payment fraud, and chain multiple attack vectors to achieve objectives.

$320k - $405k

Anthropic

As a member of the Applied AI team, you will be an Applied AI Engineer focused on becoming a trusted technical advisor to Enterprise Technology companies adopting the Claude API into their core products. You will work closely with customer product and engineering teams as they ship new products powered by Claude, advising on architecture design decisions, developing evaluation frameworks, and guiding customers through cutting-edge implementation patterns for LLMs. Working closely with our Sales, Product, and Engineering teams, you'll guide a focused portfolio of customers from technical discovery through successful deployment, combining deep engineering expertise with customer-facing skills to help customers unlock the full potential of the Claude API.

$200k - $320k

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

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

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 is seeking a Staff+ Software Engineer to enhance the vector search infrastructure powering Claude. This role is crucial for Claude's ability to access information, impacting web search, conversation memory, and model training. You will join a small, foundational team responsible for the architecture, performance, scalability, and cost of the vector database layer. As a hands-on engineer, you will contribute to coding and make key architectural decisions, shaping the future evolution of this critical system within the Databases organization.

$320k - $485k

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

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

Prime Intellect

Prime Intellect is developing an open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, integrates compute, environments, evaluations, secure sandboxes, and high-performance training for post-training at scale, including SFT, RL, tool use, agent workflows, and continuous model improvement. They are building open-source frontier AI models for long-horizon tasks and the platform their research team uses. The role focuses on building post-training and agent systems for national institutions, public-sector organizations, and regulated industries, addressing needs for models and agents that operate within strict boundaries for data, deployment, access, auditability, and human authority, while enabling self-improvement without external model dependency.

$150k - $300k

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

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training/deployment for post-training at scale, including SFT, RL, and agent workflows. They are developing open-source models for long-horizon tasks and the platform their research team uses. The company has raised significant funding and is looking for individuals passionate about frontier research, infrastructure, and go-to-market strategies in a nascent category.

$150k - $350k

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

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

Prime Intellect

Prime Intellect is building the open superintelligence stack, a full-stack system for post-training at frontier scale. Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment. We are developing open-source models trained end-to-end for long-horizon tasks and the platform our research team uses to build them. This role is for someone who wants to build at the intersection of frontier research, real infrastructure, and go-to-market for a new category. As a Research Engineer, you will build the tasks and environments that train our models through RL, and the evaluations that measure their capabilities. You will collaborate directly with researchers to diagnose model failures, examining both task implementation and success scoring.

$150k - $350k