Principal Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A, Drug disco[...]

JR United Kingdom; London; Remote; GBP 120,000 - 160,000; Full time

Job summary

A leading organization in drug discovery is seeking a Principal Machine Learning Engineer to lead structural biology models. This fully remote role offers a base salary of up to £160,000, plus equity and benefits. The successful candidate will apply their expertise in ML to tackle complex biological challenges and mentor other engineers. Responsibilities include defining data approaches, designing model extensions, and influencing technical strategy in ML for structural biology.

Benefits

Remote working culture

Stock options

Flexible hours

Qualifications

• Deep expertise in training and deploying transformer-based models.
• Experience with ML at scale, CI/CD, versioning, distributed training.

Responsibilities

• Define approaches for data preprocessing and benchmarking.
• Design and implement model extensions for protein interactions.
• Mentor team members and aid project planning.

Skills

Machine Learning

Problem Solving

Mentorship

Collaboration

Education

PhD in ML, Computational Biology, or Structural Biology

Tools

PyTorch

Docker

Kubernetes

Job description

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Principal Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A, Drug discovery | Fully Remote, EU | Base Salary Up to £160,000, plus early equity+benefits, London (City of London)

Client:

Location:

London (City of London), United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Views:

4

Posted:

12.05.2025

Expiry Date:

26.06.2025

Job Description:

Principal Machine Learning Engineer, Structural Biology | Pharma/BioTech expertise | Series A - Drug discovery B2B Platform | Fully Remote, EU | Base Salary Up to £160,000, plus early equity+benefits

The Client:

A leading organization in drug discovery seeks a Principal ML Engineer to lead their structural biology models. This role offers the chance to apply foundational models to complex biological challenges.

The candidate will work closely with leadership, serving as the technical authority on ML modeling, architecture, and experimentation. While not managing people, mentorship of engineers and researchers is expected.

Deep expertise in training and deploying transformer-based models for protein structure prediction and related tasks is required. Knowledge of their application in drug discovery workflows is essential. A proven record in strategy, problem-solving, and impactful ML system delivery is necessary.

Responsibilities include:

• Defining approaches for data preprocessing, selection, and benchmarking involving protein structures and biological datasets.
• Designing and implementing model extensions for challenges like predicting protein interactions and binding affinities.
• Mentoring team members and aiding project planning and execution.
• Leading technical strategy for ML in structural biology, focusing on foundational models.
• Influencing model architecture, data infrastructure, and deployment strategies.
• Collaborating with teams to meet scientific discovery needs.
• Contributing to publications or open-source projects.
• Developing scalable ML systems, including training, inference, and deployment pipelines.

Milestones:

• By month 3: Lead a modeling project, creating strategies and plans.
• By month 6: Deliver initial model extensions with benchmarking and pipelines.
• By month 12: Oversee multiple initiatives, demonstrating improvements and providing mentorship.

Candidate requirements:

• PhD or equivalent in ML, computational biology, or structural biology with proven application experience.
• Extensive experience with transformer models using frameworks like PyTorch.
• Understanding of data challenges and scalable workflows.
• Experience with ML at scale, CI/CD, versioning, distributed training.
• Proficiency in MLOps tools like Docker, Kubernetes, cloud platforms.
• Ability to navigate complex environments and execute ambitious projects.
• Knowledge of how structural biology models contribute to drug discovery.

Remuneration:

• Remote working culture
• Up to £160,000 base salary
• Stock options
• B2B & full-time employee options
• Flexible hours, CET +/- 3 hours

If you match the Principal Machine Learning Engineer, ADMET | Pharma/BioTech profile, send your CV for consideration!