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ML Research Engineer Jobs

Experts who push the boundaries of machine learning through cutting-edge research and development. A role that combines deep theoretical knowledge with practical application.

Open roles
21
Salary range
£90k – £635k
Hiring companies
10
View 21 live roles → Get an alert

ML Research Engineers are at the forefront of advancing machine learning technologies. They work on developing new algorithms, improving existing models, and ensuring that these innovations can be effectively deployed in real-world applications. These roles are typically found in research-heavy startups, scaleups, and the larger consultancies, where the focus is on pushing the boundaries of what's possible with machine learning.

What the role does

Inside the role of an ML Research Engineer

A typical week is split between theoretical research, coding, and collaboration with cross-functional teams.

  1. 01
    Conduct literature reviews to stay updated on the latest research.
  2. 02
    Design and implement new machine learning algorithms.
  3. 03
    Collaborate with data scientists and engineers to integrate models into products.
  4. 04
    Optimise and test models to improve performance.
  5. 05
    Document findings and contribute to research papers or internal reports.
  6. 06
    Attend meetings to discuss project progress and next steps.
Salary on the board

£90k – £635k

Based on advertised midpoints across the 6 priced listings posted in the last 12 months. Base salary only.

Salary visibility
3% of listings advertise a salary.
Skills & tools

What hiring managers ask for

% of 26 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
81%
Machine Learning
50%
PyTorch
42%
Kubernetes
23%
Deep Learning
19%
Data Pipelines
19%
Data Engineering
19%
Reinforcement Learning
19%
Diffusion Models
15%
AWS
15%
Docker
15%
CI/CD
15%
Career ladder

From Junior to Principal

A typical UK progression for ml research engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.

  1. Level 1

    Junior ML Research Engineer

    0–2 yrs

    Assist in research projects, implement basic algorithms, and contribute to team discussions.

  2. Level 2

    ML Research Engineer

    2–5 yrs

    Lead specific research initiatives, design and implement complex models, and mentor junior team members.

  3. Level 3

    Senior ML Research Engineer

    5–8 yrs

    Oversee multiple research projects, drive innovation, and contribute to strategic decision-making.

  4. Level 4

    Principal ML Research Engineer

    8+ yrs

    Lead the research direction of the organisation, publish influential papers, and guide the development of new technologies.

Pathway

How to become a ML Research Engineer

There's no single route, but most people follow some version of these steps.

  1. 1

    Academic Foundation

    Gain a strong foundation in mathematics, computer science, and machine learning through a relevant degree.

  2. 2

    Practical Experience

    Participate in internships or research assistant roles to apply theoretical knowledge in real-world settings.

  3. 3

    Specialisation

    Focus on a specific area of machine learning, such as deep learning or reinforcement learning, through advanced coursework or projects.

  4. 4

    Professional Development

    Join a research team in a startup, scaleup, or consultancy to work on cutting-edge projects and collaborate with industry experts.

  5. 5

    Leadership Roles

    Take on leadership responsibilities, such as managing research projects and mentoring junior engineers.

  6. 6

    Thought Leadership

    Become a recognised expert in the field, publishing influential research and contributing to the broader machine learning community.

Live jobs

21 live roles

See all 21 roles →

Research Engineer, Machine Learning (RL Velocity)

As a Research Engineer on the RL Velocity team, you will focus on building and improving the RL training infrastructure, identifying and removing bottlenecks, and partnering with researchers and engineering teams to enhance the efficiency and reliability of Anthropic's AI systems. This role involves high-leverage work that impacts the entire organization's ability to iterate and improve models quickly.

Anthropic London, United Kingdom £370,000 – £630,000 pa
Hybrid Permanent

Research Engineer, Pretraining

This role involves conducting research and implementing solutions in areas like model architecture, algorithms, and data processing for large language models. You will lead small projects, collaborate on larger initiatives, and optimize training infrastructure to ensure AI systems are safe, steerable, and trustworthy.

Anthropic London, United Kingdom
On-site Permanent
Synthesia logo

Principal Research Engineer

Lead the end-to-end technical direction of offline video generation for a leading AI video platform, driving large-scale generative model development from pre-training through post-training. Bridge research and product by solving cross-cutting technical challenges in training stability, data pipelines, and alignment. Coach engineers, shape team processes, and accelerate the deployment of state-of-the-art avatar video models at scale.

Synthesia London, United Kingdom
Remote Permanent
Synthesia logo

Senior Research Engineer - Video Foundation Models (Pre - Training)

Develop and scale latent video diffusion models for human-centric video generation, focusing on controllability, training stability, and inference efficiency. Work on conditioning mechanisms for pose, emotion, and script control while optimizing distributed training and evaluation frameworks. Deliver production-grade foundation models with direct impact on a widely used AI video platform.

Synthesia London, United Kingdom
Remote Permanent

Research Engineer, Pretraining Scaling - London

This role involves owning critical aspects of Anthropic's production pretraining pipeline, including performance optimization, debugging complex issues, and improving training efficiency. The position is highly operational, requiring responsiveness to incidents and flexibility during model launches, with significant learning opportunities.

Anthropic London, United Kingdom
On-site Permanent
Synthesia logo

Senior Research Engineer - Audio Post-Training

This role involves advancing high-quality, expressive synthetic voice generation through post-training optimization of AI models. The engineer will work on fine-tuning speech models using techniques like DPO and LoRA, implementing efficiency improvements such as quantization and distillation, and integrating novel architectures like neural codecs and diffusion models. The position is embedded in a research-driven team focused on real-time, production-grade voice synthesis for global enterprise applications.

Synthesia London, United Kingdom
Remote Permanent
Synthesia logo

Senior Research Engineer - Data

This role focuses on building and enhancing large-scale data pipelines for AI model training, working with vast video and audio datasets to improve data quality, curation, and annotation. The position bridges applied research and data engineering, collaborating closely with model teams to extract meaningful features and drive performance gains. It emphasizes clean, maintainable code and influence over long-term data infrastructure strategy.

Synthesia London, United Kingdom
Remote Permanent
Synthesia logo

Senior Research Engineer - Interactive Avatars

This role involves developing advanced AI models for interactive avatars, focusing on diffusion-based video generation conditioned on audio, motion, and user interaction. The engineer will work on real-time, long-form video synthesis, improving lip-sync and motion realism, and building evaluation systems to ensure high visual quality. The position bridges cutting-edge research and product deployment within a fast-moving AI video platform.

Synthesia London, United Kingdom
Remote Permanent
See all 21 roles →
Top hirers

Companies hiring ml research engineers

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Hiring locations

Where this role is hiring

The locations with the most live listings for this role today.

London

Location
19 open

Southampton

Location
2 open

Cambridge

Location
1 open
FAQs

Common questions

  • A strong background in computer science, mathematics, or a related field is essential. Advanced degrees, such as a Master's or PhD, are often required for higher-level positions.

  • Key skills include proficiency in programming languages like Python, a deep understanding of machine learning algorithms, and the ability to conduct rigorous research and experimentation.

  • The typical progression starts with a junior role, advancing to a senior position, and eventually leading to principal or leadership roles within the organisation.

  • Common industries include tech, finance, healthcare, and academia. Research-heavy startups and scaleups are also significant employers.

  • Salaries can vary widely based on experience, location, and industry. For more detailed salary information, please refer to the salary section on this page.

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