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Machine Learning Scientist Jobs

Experts who design, build, and optimise machine learning models to solve complex problems. A role that combines deep technical knowledge with a creative approach to data-driven solutions.

Open roles
6
Hiring companies
5
View 6 live roles → Get an alert

Machine Learning Scientists are at the heart of the AI revolution, driving innovation through the development and deployment of advanced machine learning models. These roles are found in a variety of settings, from research-heavy startups to large tech companies and academic institutions. ML Scientists work on a wide range of projects, from developing cutting-edge algorithms to improving the efficiency and accuracy of existing models. They often collaborate with data engineers, software developers, and domain experts to bring their models to life and ensure they deliver real-world impact.

What the role does

Inside the role of a Machine Learning Scientist

A typical week for a Machine Learning Scientist is a mix of research, experimentation, and collaboration. They spend time coding, analysing data, and refining models.

  1. 01
    Design and implement machine learning algorithms.
  2. 02
    Analyse and preprocess large datasets.
  3. 03
    Collaborate with cross-functional teams to integrate models.
  4. 04
    Conduct experiments and validate model performance.
  5. 05
    Document findings and present results to stakeholders.
  6. 06
    Stay updated with the latest research and techniques.
Skills & tools

What hiring managers ask for

% of 7 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Machine Learning
86%
PyTorch
71%
Deep Learning
43%
Python
43%
TensorFlow
43%
JAX
43%
NumPy
29%
SciPy
29%
Pandas
29%
Graph Neural Networks
29%
Generative Models
29%
Generative Modeling
14%
Career ladder

From Junior to Principal

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

  1. Level 1

    Junior Machine Learning Scientist

    0–2 yrs

    Assist in data preprocessing and model training, with guidance from senior team members.

  2. Level 2

    Machine Learning Scientist

    2–5 yrs

    Lead the development of machine learning models, from design to deployment, and contribute to research efforts.

  3. Level 3

    Senior Machine Learning Scientist

    5–8 yrs

    Oversee multiple projects, mentor junior scientists, and drive innovation in model development and optimisation.

  4. Level 4

    Principal Machine Learning Scientist

    8+ yrs

    Strategise and lead the overall direction of machine learning initiatives, influence company-wide AI strategy, and collaborate with external partners.

Pathway

How to become a Machine Learning Scientist

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

  1. 1

    Academic Foundation

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

  2. 2

    Practical Experience

    Build practical skills through internships, personal projects, or contributions to open-source projects.

  3. 3

    Specialisation

    Focus on a specific area of machine learning, such as deep learning, reinforcement learning, or natural language processing.

  4. 4

    Professional Development

    Continue learning through advanced courses, certifications, and staying updated with the latest research.

  5. 5

    Leadership Roles

    Take on leadership responsibilities, mentor junior scientists, and drive strategic initiatives.

  6. 6

    Industry Impact

    Influence the broader industry through thought leadership, publications, and collaborations with leading institutions.

Live jobs

6 live roles

Machine Learning Scientist

This role involves designing and prototyping novel generative machine learning models for protein design, with close collaboration between computational and experimental teams. The scientist will build scalable data pipelines, optimize deep learning models for performance, and iteratively refine models based on wet lab feedback. A strong emphasis is placed on code quality, interdisciplinary collaboration, and translating model outputs into real-world biological functions.

Latent Labs London, United Kingdom, United Kingdom
Hybrid Permanent

Machine Learning Scientist

Develop novel machine learning methods for molecular and protein discovery, bridging cutting-edge research with practical engineering implementation. Work on geometric deep learning, diffusion models, and 3D representations in biological systems, translating scientific ideas into deployable tools. Collaborate closely with engineers and scientists in a hybrid London-based role focused on high-impact AI for life sciences.

Platform Recruitment London, United Kingdom £85,000 – £100,000 pa

Machine Learning Scientist – Sequence Modelling

A Machine Learning Scientist will develop and apply advanced sequence modelling techniques to DNA and genetic data to uncover associations between genetic variants and diseases. The role involves building and evaluating ML models for variant interpretation, gene discovery, and regulatory modelling, in close collaboration with computational and experimental scientists. Work is grounded in real-world therapeutic discovery, leveraging both internal and large-scale external genomics datasets.

Relation Therapeutics London, United Kingdom
Permanent

Senior Machine Learning Scientist (Single Cell)

Develop machine learning models tailored to single-cell and multiomic biological data to understand cellular responses to interventions and inform therapeutic strategies. Work at the intersection of generative modelling and experimental biology, collaborating closely with wet-lab scientists to translate biological questions into modelling problems and interpret results in meaningful ways. Contribute to the research roadmap and advance the biological coherence of model evaluation beyond standard metrics.

Relation Therapeutics London, United Kingdom
On-site Permanent
Isomorphic Labs logo

Research Scientist (Machine Learning), London

A Research Scientist in Machine Learning will develop novel deep learning models and algorithms to accelerate drug discovery, working in a cross-disciplinary environment with scientists and engineers. The role involves designing architectures, training models, and applying cutting-edge ML techniques to biological and chemical problems, with opportunities to lead projects and mentor others depending on experience.

Isomorphic Labs London, United Kingdom
Hybrid Permanent

Senior/Principal Machine Learning Scientist (Generative Modelling)

This role involves developing generative and predictive models of cellular behaviour using single-cell multi-omics and perturbation data, with a focus on causal inference, counterfactual prediction, and guiding experimental design. The scientist will work iteratively with wet-lab teams to validate hypotheses and refine models, operating at the intersection of machine learning and experimental biology. The position emphasizes mechanistic fidelity, real-world utility, and interdisciplinary collaboration in a high-impact drug discovery environment.

Relation Therapeutics London, United Kingdom
On-site Permanent
Hiring locations

Where this role is hiring

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

London

Location
7 open
FAQs

Common questions

  • Essential skills include strong programming abilities, a deep understanding of algorithms and data structures, and proficiency in statistical analysis and machine learning frameworks.

  • A PhD is highly valued but not always required. Many successful Machine Learning Scientists have a master's degree and extensive practical experience.

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

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

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