Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Benefits
Joblaze summary
In this role, the Research Engineer will focus on enhancing the RL training infrastructure that supports researchers at Anthropic, streamlining processes to boost efficiency and reliability. Key skills include strong software engineering fundamentals and experience with machine learning infrastructure, particularly in distributed systems. This position is ideal for candidates with a background in ML tooling who thrive in collaborative environments and are eager to facilitate the work of others. Anthropic emphasizes a cohesive team approach, aiming for impactful AI research through shared large-scale efforts.
Joblaze insights
- Listed about a month ago on Joblaze — tracked directly from Anthropic's career page.
- Anthropic has 413 other open roles including Product Manager, Platform, Policy Counsel, EMEA , Staff+ Security Engineer, Risk Engineering.
- 1675 active AI/ML roles on Joblaze right now.
- 170 active PyTorch roles on Joblaze right now.
- 45 active JAX roles on Joblaze right now.
- Salary band is above the typical range for AI/ML roles (median ~$190,900).
Quick facts
- Is the Research Engineer, Machine Learning (RL Velocity) role remote?
- It's hybrid — Anthropic expects some on-site time in London, UK.
- What's the salary range?
- Anthropic lists £370,000–£630,000 for this role.
- Where is the role based?
- Anthropic is hiring for this position in London, UK.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: JAX, AI/ML, PyTorch.
- Does Anthropic sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Anthropic targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Engineer, Machine Learning (RL Velocity) role at Anthropic.
From the original posting
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run.
Responsibilities
- Build and improve the RL training infrastructure that researchers depend on day-to-day
- Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed
- Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster
- Own the reliability and performance of research runs end-to-end
- Contribute to design decisions that shape how Anthropic does RL at scale
You may be a good fit if you
- Have strong software engineering fundamentals and a track record of building performant, reliable systems
- Have worked on ML infrastructure, distributed systems, or research tooling
- Care about enabling other people's work and find leverage through platforms rather than individual experiments
- Are comfortable operating across the stack, from low-level performance work to RL algorithms
- Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego
Strong candidates may also have
- Experience with large-scale distributed training (RL, pre-training, or post-training)
- Familiarity with JAX, PyTorch, or similar ML frameworks
- A track record of operating at the edge of research and infra in a fast-moving environment
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.