_{23rd January, 2026}

Job Title
Senior Staff Machine Learning Engineer (Human Health) — Technical Lead
Senior Staff / Principal IC (technical leadership without people-management required; may include mentorship and dotted-line leadership)
  
We are recruiting for a Senior Staff ML Engineer to build the technical backbone that allows scientists to train frontier causal/mechanistic models on multi-omics data at scale.
  
You will lead the design and deployment of state-of-the-art ML systems that meaningfully improve human health—translating research breakthroughs to help increase the probability of success in bringing treatments to patients.
  
What You’ll Do (Core Responsibilities)

• Technical leadership: Own end-to-end architecture for one or more flagship ML capabilities (e.g., representation learning for multimodal biomedical data, foundation models for health, target discovery, biomarker discovery, imaging models, genomics models).
• Research-to-production translation: Partner with research scientists to harden prototypes into robust, measurable, reproducible systems.
• Model development: Design, train, evaluate, and iterate on deep learning models (transformers, diffusion, GNNs, multimodal models), including scaling strategies and ablations.
• MLOps and deployment: Build and own training/inference infrastructure, CI/CD for ML, monitoring, drift detection, and rollback strategies.
• Cross-functional influence: Work closely with other groups in computational sciences,.
• Mentorship: Raise the bar through design reviews, model reviews, playbooks, and mentoring senior engineers/scientists.

  
Requirements

• 10+ years software/ML engineering experience (or equivalent), including leadership on high-impact ML systems.
• Deep hands-on expertise in modern ML (deep learning, representation learning, generative models, self-supervised learning) and at least one domain: health/biomed, large-scale ML platforms, or safety-critical ML.
• Strong proficiency in Python and ML frameworks (JAX/TF/PyTorch), and ability to write production-quality code.
• Experience with large-scale training (distributed training, accelerators, performance profiling, reliability).
• Track record of driving ambiguous projects to success across multiple stakeholders.
• Excellent communication: can explain tradeoffs to researchers, engineers, product, and key stakeholders.
• Genomics & Drug Discovery ML: variant effect, protein/structure, target discovery, biomarker discovery.

  
KEMIO Consulting is leading this retained search and would welcome confidential discussions with senior candidates. Please Apply or get in touch with Eugene @ KEMIO Consulting to discuss this opportunity in more detail.
MLOps, GPU, Distributed infrastructure, Omics, London, AI/ML, Durg Discovery, Senior Staff Machine Learning Engineer, Technical Lead, ML Expert
  
  

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