Senior Machine Learning Research Engineer

About the role

Relation is a TechBio company leveraging single-cell multi-omics and machine learning to discover new therapies for devastating diseases. As a Senior Machine Learning Research Engineer, you will act as a bridge between theory and implementation by designing, building, and scaling the complex systems required for generative and predictive models of cellular behaviour. You will work in an interdisciplinary team to translate research prototypes into production-grade systems.

Responsibilities

• Implement and optimise large neural network models, partnering with ML Scientists to create 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 across multi-GPU and multi-node configurations.
• Build and maintain core ML infrastructure and contribute to architectural and algorithmic decisions.
• Optimise inference and downstream deployment for use in discovery workflows.
• Address numerical, performance, and reliability issues across the stack and establish engineering practices in research code.

Required skills

• Python
• PyTorch
• Machine Learning
• Deep Learning
• Distributed training
• GPU profiling
• Cloud ML infrastructure
• Containerised environments

Nice to have

• CUDA
• Triton kernel development
• FlashAttention
• Foundation models
• Open-source ML contributions

Qualifications

• Degree in Computer Science, Engineering, Physics, or a related quantitative discipline
• Industry experience as an ML or research engineer working on large neural network training

About the Company

Relation is a sector-defining TechBio company developing transformational medicines with technology at its core. The company leverages single-cell multi-omics, functional assays, and machine learning to drive disease understanding from cause to cure.