data science Work, Jobs in london, eng (with Salaries)

Research Engineer, Machine Learning (RL Velocity)
Anthropic —London
- £370,000 - £630,000 a year
- Hybrid work
- Bachelor's degree
- Machine learning
- Communication skills
- Flexible schedule
Research Assistant – Data
University College London —London
- £39,148 a year
- Full-time
- Data analysis skills
- Communication skills
- Time management
- Annual leave
- Employee assistance programme
8d
Bioinformatician in Infectious Diseases
Guy's and St Thomas' NHS Foundation Trust —London
- £58,133 - £65,261 a year
- Full-time
- Communication skills
6d
Research Engineer, Machine Learning (Reinforcement Learning)
Anthropic —London
- £260,000 - £630,000 a year
- Hybrid work
- System design
- Master's degree
- C++
- Flexible schedule
Senior Machine Learning Researcher
Longshot Systems Ltd —London
- Full-time
- Hybrid work
- Doctoral degree
- Master's degree
- Maths
- Gym membership
Quick apply
Quantitative Researcher (Intern)
MerQube Inc —London
- SQL
- Machine learning
- Internship
Data Analytics Lab Trainer
Ekascloud —London
- £25,000 - £35,000 a month
- Full-time
- Microsoft Excel
- Computer Science
- Data analysis skills
Graduate Machine Learning Researcher
Longshot Systems Ltd —London
- Full-time
- Hybrid work
- Doctoral degree
- Master's degree
- Maths
- Gym membership
Quick apply
7d
Director, Machine Learning Science - Content AI
Expedia —London
- £242,000 - £387,000 a year
- Full-time
- Management
- Doctoral degree
- Computer Science
- Annual leave
- Employee assistance programme
Quantitative Trading & Research - Automated Trading Strategies - Rates - Analyst or Associate
JPMorganChase —London
- Full-time
- Computer Science
- Java
- C++
Programme Delivery Manager - HR Data, Technology & AI Lab
Department for Transport —London
- £57,515 a year
- Part-time
- Hybrid work
- Presentation skills
- Travel
- Leadership
- Annual leave
- Employee assistance programme
1d
Analytics Manager - Marketing Science
Wise Australia Investments —London
- £75,000 - £115,000 a year
- Management
- SQL
- Project management
- Life insurance
Machine Learning Scientist II
Expedia —London
- Full-time
- Doctoral degree
- Computer Science
- Master's degree
3d
London - Long Internship 2026 - Prime Services Quantitative Research
BNP Paribas —London
- Full-time
- Hybrid work
- Doctoral degree
- Computer Science
- Java
- Employee assistance programme
Environment Construction Engineer, AWS Data Center Environment
Amazon Data Services UK Limited —London
- Full-time
- Master's degree
- AWS
- Bachelor's degree
5d
Machine Learning Scientist, Ranking
Depop —London
- Full-time
- Hybrid work
- Azure
- AWS
- Machine learning
- Employee assistance programme
- Life insurance
Machine Learning Scientist
Depop —London
- Full-time
- Hybrid work
- Azure
- AWS
- Machine learning
- Employee assistance programme
- Life insurance
Staff Machine Learning Scientist - Core ML
Depop —London
- Full-time
- Hybrid work
- Azure
- AWS
- Machine learning
- Employee assistance programme
- Life insurance
Quantitative Researcher – Postgraduate
G-Research —London
- Bar
- Doctoral degree
- Master's degree
Quantitative Researcher | Trading Team
Jump Trading —London
- Full-time
- Doctoral degree
- Master's degree
- C++

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Research Engineer, Machine Learning (RL Velocity)

Anthropic -
London

Apply Now

Job details

£370,000 - £630,000 a year

Benefits

UK visa sponsorship
Flexible schedule

Qualifications

PyTorch
Bachelor's degree
Machine learning
Distributed systems
Communication skills

Full job description

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.

Annual Salary:

£370,000 - £630,000 GBP

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.

Apply Now

Refine Your Search

data science jobs in london, eng

Research Engineer, Machine Learning (RL Velocity)

Research Assistant – Data

Bioinformatician in Infectious Diseases

Research Engineer, Machine Learning (Reinforcement Learning)

Senior Machine Learning Researcher

Quantitative Researcher (Intern)

Data Analytics Lab Trainer

Graduate Machine Learning Researcher

Director, Machine Learning Science - Content AI

Quantitative Trading & Research - Automated Trading Strategies - Rates - Analyst or Associate

Programme Delivery Manager - HR Data, Technology & AI Lab

Analytics Manager - Marketing Science

Machine Learning Scientist II

London - Long Internship 2026 - Prime Services Quantitative Research

Environment Construction Engineer, AWS Data Center Environment

Machine Learning Scientist, Ranking

Machine Learning Scientist

Staff Machine Learning Scientist - Core ML

Quantitative Researcher – Postgraduate

Quantitative Researcher | Trading Team

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