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Senior MLOps Engineer: Production AI Biomedical R&D

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: KEMIO Consulting
Full Time position
Listed on 2026-09-02
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 90000 - 130000 GBP Yearly GBP 90000.00 130000.00 YEAR
Job Description & How to Apply Below
Position: Senior MLOps Engineer: Production AI for Biomedical R&D
Location: Greater London

A leading global life sciences organisation is expanding its AI capabilities and is looking for a Senior MLOps Engineer to help move advanced machine learning models from research into reliable, scalable production.

This is not a conventional platform engineering role.

You will sit at the intersection of AI engineering, large-scale machine learning and biomedical R&D, supporting models that may influence decisions around therapeutic targets, disease indications and patient populations.

What you’ll be responsible for :

* Owning production ML models across deployment, monitoring, retraining and lifecycle management

* Operating and troubleshooting distributed training and fine-tuning workloads

* Managing experiment tracking, model registries and full model provenance

* Deploying and optimising model-serving endpoints

* Supporting structured handover from ML engineering into production

* Driving strong MLOps standards across a highly technical AI environment

What we’re looking for

Strong hands-on experience with production ML systems, ideally including:

** PyTorch Distributed, Deep Speed, FSDP or Ray Train**

** MLflow, Weights & Biases or equivalent**

** CI/CD for ML workflows**

** Terraform or similar infrastructure-as-code tooling**

Experience with distributed GPU workloads, multimodal ML, biomedical AI, computational biology, genomics, imaging or multi-omics would be particularly relevant.

Life sciences experience is valuable, but not essential. What matters most is the ability to operate technically demanding ML systems reliably at scale.

Why this role?

The challenge is not simply getting models into production.

It is ensuring advanced scientific AI remains reproducible, trustworthy, performant and useful once it gets there.

Interested in working at the intersection of production AI and real-world drug discovery?

Get in touch with Team @KEMIO Consulting for a confidential discussion.

#MLOps #Machine Learning #Artificial Intelligence #Drug Discovery #Biotech #Life Sciences #AIEngineering

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Position Requirements
10+ Years work experience
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