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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
4
Hiring companies
3
View 4 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%
TensorFlow
43%
JAX
43%
Python
43%
NumPy
29%
SciPy
29%
Pandas
29%
Graph Neural Networks
29%
Generative Models
29%
Reinforcement Learning
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

4 live roles

Machine Learning Scientist

This role involves developing and prototyping generative machine learning models for protein design, with a strong focus on real-world biological applications. You'll work closely with biologists and engineers to build robust data pipelines, optimize model performance, and translate model outputs into wet lab testing campaigns. The position requires deep expertise in generative modeling, production-level ML coding, and iterative learning from experimental feedback.

Latent Labs London, United Kingdom, United Kingdom
Hybrid Permanent

Machine Learning Scientist – Sequence Modelling

About RelationRelation is an end-to-end biotech company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly...

Relation Therapeutics London, United Kingdom
Permanent
Isomorphic Labs logo

Research Scientist (Machine Learning), London

A Research Scientist in Machine Learning will develop novel deep learning models and algorithms to advance drug discovery at Isomorphic Labs. The role involves interdisciplinary collaboration with scientists and engineers to design, train, and scale AI systems that model complex biological and chemical problems. The position emphasizes innovation in model architecture, experimentation, and the application of cutting-edge machine learning to accelerate the development of life-changing medicines.

Isomorphic Labs London, United Kingdom
Hybrid Permanent
Isomorphic Labs logo

Research Scientist (Machine Learning), Lausanne

A Research Scientist in Machine Learning will develop novel AI models and algorithms to accelerate drug discovery, working in an interdisciplinary team of scientists and engineers. The role involves designing deep learning architectures, training models on biological and chemical data, and collaborating across disciplines to solve complex problems in computational biology and chemistry.

Isomorphic Labs United Kingdom
Hybrid Permanent
Hiring locations

Where this role is hiring

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

London

Location
3 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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