Senior Machine Learning Research Engineer

Relation
London
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Communication","Ownership","Stakeholder management","Collaboration","Problem-solving"]

Build and scale generative and predictive models of cellular behaviour by bridging ML research and production engineering. Implement and optimise large neural networks with reproducible training pipelines, profile GPU workloads, and design distributed multi-GPU/multi-node training strategies. Develop and maintain core ML infrastructure, improve inference and downstream deployment, and partner with ML Scientists to take prototypes to robust, reusable systems for large multi-modal biological data.

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FursaFursa
Relation
Relation
15 hours ago

Senior Machine Learning Research Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 6 hours agoStatus: Live

Job Summary

Build and scale generative and predictive models of cellular behaviour by bridging ML research and production engineering. Implement and optimise large neural networks with reproducible training pipelines, profile GPU workloads, and design distributed multi-GPU/multi-node training strategies. Develop and maintain core ML infrastructure, improve inference and downstream deployment, and partner with ML Scientists to take prototypes to robust, reusable systems for large multi-modal biological data.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Implement and optimise large neural network models, partnering with ML Scientists to deliver reproducible, scalable training pipelines.
  • •Profile and optimise training across compute, memory, and I/O to improve throughput, convergence, and stability.
  • •Design and implement distributed training strategies for multi-GPU and multi-node configurations.
  • •Build and maintain core ML infrastructure and contribute to architectural and algorithmic decisions in research discussions.
  • •Optimise inference and downstream deployment, addressing numerical, performance, and reliability issues across the stack.

Key Requirements

  • •Degree in Computer Science, Engineering, Physics, or a related quantitative discipline; industry experience as an ML/research engineer training large neural network models.
  • •Strong software engineering fundamentals in Python and deep expertise in PyTorch (or equivalent modern ML frameworks).
  • •Hands-on experience training large neural networks at scale, including distributed training frameworks.
  • •Demonstrable experience profiling and optimising GPU workloads.
  • •Working knowledge of cloud-based ML infrastructure and containerised environments.
Education:Bachelor's in Computer Science, Engineering, Physics, or related quantitative discipline
Skills:CommunicationOwnershipStakeholder managementCollaborationProblem-solving
Tech Stack:PythonPyTorchCUDATritonFlashAttentionCloud-based ML infrastructureContainersMulti-GPUMulti-nodeDistributed training

Company Brief

Relation
Relation (Relation Therapeutics) is a UK-based, technology-enabled biopharmaceutical company that combines single-cell multi-omics, patient-derived tissue, functional assays and machine learning to discover and develop novel therapeutics across immunology, metabolic and bone diseases.
Industry: Biotech
Company Size: Medium (51 to 250 employees)
Growth: Early Stage Startup
Valuation: USD 100M to 250M
Funding: Seed
Headquarters: London, United Kingdom
Founded: 2019
Glassdoor
Glassdoor: 3.8
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