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Machine Learning Engineer

London
£90k – £120k/yr
Posted about 21 hours ago
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Job Title: Machine Learning Engineer, Protein Design

Location: London (Hybrid)

Salary: Up to £120,000 DOE

A well-funded biotechnology company working at the frontier of AI-driven protein design is looking for a Machine Learning Engineer to help build and deploy the systems that power their discovery platform.

This is a hands-on engineering role sitting at the intersection of machine learning and structural biology. You will work closely with ML scientists and computational biologists to take research prototypes into production, building scalable infrastructure for training, inference, and evaluation across molecular and protein datasets. The problems are genuinely hard and the domain is one of the most exciting applications of ML in science today.

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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

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Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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What we are looking for

  • MSc or PhD in Computer Science, Machine Learning, Computational Biology, Bioinformatics, or a related field, or equivalent industry experience
  • Strong Python software engineering skills with experience in PyTorch or JAX
  • Demonstrable experience deploying ML models into production environments
  • Knowledge of MLOps, containerisation, Docker, CI/CD, cloud platforms, and model serving
  • Experience optimising model training and inference for performance and scalability
  • Comfortable working in a fast-moving, multidisciplinary environment alongside scientists and engineers

Particularly strong candidates will also have

  • Experience working with protein structures, molecular datasets, or biological sequence data
  • Familiarity with graph neural networks, geometric deep learning, equivariant architectures, or diffusion models applied to proteins
  • Experience with distributed training, GPU optimisation, or high performance computing
  • Knowledge of protein structure prediction, docking, or generative models for protein design
  • Familiarity with tools such as AlphaFold, RoseTTAFold, or similar structure prediction frameworks

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Why this role

You will be joining a team using machine learning to solve one of the hardest problems in biology, with real scope to influence how the engineering infrastructure is built and scaled. The salary reflects both the seniority and the domain expertise expected.

This role requires existing right to work in the UK.

If your background fits, apply below.

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Skills

Python
PyTorch
JAX
MLOps
Docker
CI/CD
Cloud Platforms
Model Serving
Protein Design
Graph Neural Networks
Geometric Deep Learning
Equivariant Architectures
Diffusion Models
Distributed Training
GPU Optimisation
High Performance Computing

Location

London, England, United Kingdom

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