ML Platform Engineer for Multi-Omics & Precision Medicine in London

ML Platform Engineer for Multi-Omics & Precision Medicine in London

London Full-Time 60750 - 74250 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Design and maintain a cutting-edge multi-omics AI platform for healthcare diagnostics.
  • Company: Join Panakeia, a fast-growing team at the forefront of precision medicine.
  • Benefits: Enjoy hybrid work, equity options, and a competitive salary.
  • Other info: Collaborate with diverse teams in a dynamic and supportive environment.
  • Why this job: Make a real impact in healthcare by developing innovative AI solutions.
  • Qualifications: Experience with Python, PyTorch, and building ML pipelines is essential.

The predicted salary is between 60750 - 74250 £ per year.

Panakeia is hiring an ML Platform Engineer to join a fast-growing, cross-disciplinary team.

You will design and maintain a multi-omics AI platform, building data and ML pipelines, and collaborating with product, research and engineering to deliver high‑quality AI-based diagnostics.

The role emphasizes producing production‑readied ML systems from research, using Python and Py Torch, with cloud, hybrid and on‑prem deployments, in a healthcare‑focused setting.

Hybrid work and equity are offered.

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ML Platform Engineer for Multi-Omics & Precision Medicine in London employer: Panakeia

At Panakeia, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our employees to thrive in the rapidly evolving field of multi-omics and precision medicine. Our commitment to hybrid work arrangements, competitive equity options, and continuous professional development ensures that you will not only contribute to groundbreaking AI-based diagnostics but also grow your career in a supportive environment dedicated to making a meaningful impact in healthcare.

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Contact Details:

Panakeia Recruitment Team

We think you need these skills to ace ML Platform Engineer for Multi-Omics & Precision Medicine in London

Machine Learning
Python
PyTorch
Data Pipeline Development
Cloud Computing
Hybrid Deployment
On-Premise Deployment