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

JR United Kingdom; Leigh; Remote; GBP 125,000 - 150,000; Full time

Job summary

An established industry player in the drug discovery sector is seeking a Principal Machine Learning Engineer to lead innovative projects in structural biology. This fully remote role offers a unique opportunity to apply advanced machine learning techniques to real-world challenges in drug discovery. The successful candidate will design and implement cutting-edge models, mentor a talented team, and influence key decisions in a collaborative environment. If you are passionate about leveraging machine learning to make a significant impact in the pharmaceutical industry, this role is perfect for you.

Qualifications

• Deep expertise in training and deploying transformer-based models for protein structure prediction.
• Experience in designing scalable workflows for data preprocessing and evaluation.

Responsibilities

• Lead the technical strategy for machine learning applications in structural biology.
• Mentor team members and assist with complex projects related to structural biology modeling.

Skills

Machine Learning

Transformer Models

Structural Biology

Data Preprocessing

Mentorship

Problem Solving

Education

PhD in Machine Learning or Computational Biology

Equivalent Experience

Tools

PyTorch

Docker

Kubernetes

CI/CD Pipelines

Job description

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Principal Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A - Drug discovery B2B Platform | Fully Remote, EU | £ 850-1200pd, Outside IR35 | 6-12 months Contract Length, Leigh

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Client:

Location:

Leigh, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

4

Posted:

28.04.2025

Expiry Date:

12.06.2025

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Job Description:

Principal Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A - Drug discovery B2B Platform | Fully Remote, EU | £ 850-1200pd, Outside IR35 | 6-12 months Contract Length

The Client:

A leading organization in the drug discovery field is currently looking for a Principal ML Engineer to spearhead the technical direction for their structural biology models. This hands-on, high-impact role offers the opportunity to advance the application of foundational models to complex structural biology challenges.

The successful candidate will work closely with the leadership team, serving as the technical authority on machine learning modeling, architecture, and experimentation in this domain. While this role does not involve people management, the candidate will be expected to provide mentorship and guidance to engineers and researchers on technical content.

The ideal candidate will have deep expertise in training and deploying transformer-based models for protein structure prediction and related tasks. Additionally, they should have a strong understanding of how these models are applied within drug discovery workflows. A proven track record in setting strategy, solving complex technical problems, and delivering impactful ML systems is essential.

Principal Machine Learning Engineer, Structural Biology | Pharma/BioTech expertise | Series A - Drug discovery B2B Platform | Fully Remote, EU || £ 850 - 1200pd, Outside IR35 | 6 - 12 months Contract Length

• Define approaches for data preprocessing, selection, and benchmarking for new training tasks involving protein structures, complexes, and multimodal biological datasets.
• Design and implement extensions to models tailored to specific challenges, such as predicting protein complex interactions and binding affinities, including data processing, benchmarking, and evaluation pipelines.
• Provide mentorship and guidance to team members, assisting with the planning and execution of complex projects related to structural biology modeling.
• Lead the technical strategy for machine learning applications in structural biology, focusing on adapting and expanding foundational models such as those for protein folding and related tasks.
• Influence key decisions regarding model architecture, data infrastructure, and model deployment strategies.
• Work collaboratively with other teams to ensure models address practical needs in scientific discovery.
• Contribute to scientific publications or open-source projects where applicable.
• Develop and maintain scalable, production-ready machine learning systems, including pipelines for training, inference, and deployment.

Expected Milestones

• By month 3: Take charge of a structural biology modeling project. Create a strategy and experiment plan for adapting foundational models to a key high-value application.
• By month 6: Deliver the initial functional model extension (e.g., binding affinity prediction head), complete with a clear benchmarking framework and a replicable pipeline.
• By month 12: Oversee multiple ML initiatives in structural biology, showcasing significant improvements in model accuracy and practical impact. Provide mentorship to peers and set the strategic direction for the area.nd practical impact. Provide mentorship to peers and set the strategic direction for the area.

Principal Machine Learning Engineer, Structural Biology | Pharma/BioTech expertise | Series A - Drug discovery B2B Platform | Fully Remote, EU || Fully Remote, EU | £ 850 - 1200pd, Outside IR35 | 6 - 12 months Contract Length

• You hold a PhD (or equivalent experience) in machine learning, computational biology, or structural biology, with a proven track record of applying machine learning to real-world protein structure or drug discovery challenges.
• You have extensive experience in building and training transformer-based models (e.g., protein folding models) using frameworks like PyTorch, PyTorch Lightning, or similar.
• You understand the data challenges in structural biology and are capable of designing scalable preprocessing, training, and evaluation workflows.
• You have experience delivering machine learning systems at scale, including CI/CD pipelines, model versioning, and distributed GPU-based training.
• You are proficient with modern MLOps tools and infrastructure, such as Docker, Kubernetes, cloud platforms, and orchestration tools.
• You are adept at navigating complex technical environments and can deconstruct and execute ambitious modeling initiatives.
• You understand how structural biology models contribute to the drug discovery process and can align your work with real-world applications.

If you think you are a good match for the Principal Machine Learning Engineer, ADMET | Pharma/BioTech expertise, ping us over your CV and we will give you a call if we think you are a good match!