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Company

About Us

Our story, mission & values

Insights

Articles, case studies & news

Contact

Get in touch with our team

Solutions

All Solutions

Engage+, Amplify & Access

Engage+

Prioritised executive search

Amplify

Project-based & scalable hiring

Access

Exclusive contingent search

Specialisms

BioTech

Biological science creating breakthroughs

MedTech

Medical technology shaping healthcare

TechBio

Digital innovation driving discovery

Pharma

Medicines development changing lives

Featured Role

Now Hiring

Computational Scientist - Chemistry / Cheminformatics

San Francisco, United States · TechBio · Full Time

View role →

Looking for your next role in life sciences?

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Senior Machine Learning Engineer

London, UK

One of Europe’s most exciting AI-driven healthcare startups is scaling their technical team. Backed by top-tier investors and partnered with global tech providers, this company is transforming how life sciences and healthcare teams access and utilise critical biomedical, clinical, and regulatory knowledge.

As they continue to develop their next-gen AI platform, they’re now looking to bring in a Senior Machine Learning Engineer with strong expertise in deep learning, LLMs, and generative AI to help lead key product innovation and infrastructure at scale.

This is an opportunity to work on genuinely meaningful technology with a talented, mission-driven team at the forefront of AI in life sciences.

What you’ll be working on

This role sits at the intersection of deep learning R&D, LLM system design, and production ML. You’ll help architect and deliver the infrastructure that powers real-time biomedical insight at scale.

Key responsibilities

  • Research, train, fine-tune, and evaluate LLMs (e.g. GPT, LLaMA, Mistral) for biomedical and regulatory use cases.
  • Implement model adaptation strategies (LoRA, QLoRA, PEFT, RLHF, etc.) for domain-specific tasks.
  • Build RAG pipelines combining retrieval and generation with robust safety and performance guardrails.
  • Develop and maintain scalable training and inference infrastructure in the cloud (e.g. GCP Vertex AI, AWS SageMaker).
  • Work cross-functionally with engineering, product, and domain experts to translate research goals into applied ML features.
  • Champion privacy-first, compliant ML systems that align with healthcare regulations (GDPR, HIPAA, GxP).
  • Mentor junior engineers and influence the technical roadmap as a core part of the leadership team.
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