ML Infrastructure Engineer – Large-Scale Imaging

MRC Laboratory of Molecular Biology (LMB); Cambridge; On-site; GBP 52,000 - 61,000; Full time

Benefits offered by this job

Pension scheme

40.5 days holiday

On-site parking

Staff restaurant

Campus nursery

Training & development

Job summary

MRC Laboratory of Molecular Biology (LMB) in Cambridge, UK seeks a Machine Learning Engineer specialising in deployment and infrastructure to support connectomics. The role focuses on deploying, scaling and maintaining ML models for volume electron microscopy, including automated segmentation and synapse detection.

The ideal candidate will have a PhD or MSc/MPhil with strong Python and ML framework experience, plus extensive work with large-scale data, Linux, containers, and HPC environments.

Qualifications

• PhD in computer science, engineering, data science, computational biology, physics, mathematics or a related quantitative discipline, or MSc / MPhil plus significant experience in ML engineering, infrastructure engineering or large-scale data processing.
• Strong Python engineering skills; experience with PyTorch and TensorFlow.
• Experience deploying ML models in production or production-like environments; handling large-scale data (multi-terabyte or petabyte scale).

Responsibilities

• Deploy, scale and maintain ML models for volume electron microscopy.
• Build reliable production workflows across GPU/CPU clusters, large storage systems and HPC environments.
• Ensure models are reproducible, monitored and debuggable in execution.
• Work with Linux systems, containers, and workflow orchestration.

Skills

Python programming

PyTorch

TensorFlow

Linux

GPU infrastructure

HPC environments

Containers

Workflow orchestration

Education

PhD or MSc/MPhil in a related field

Tools

Containers

Workflow orchestration

Job description

MRC Laboratory of Molecular Biology (LMB) in Cambridge, UK seeks a Machine Learning Engineer specialising in deployment and infrastructure to support connectomics. The role focuses on deploying, scaling and maintaining ML models for volume electron microscopy, including automated segmentation and synapse detection.

The ideal candidate will have a PhD or MSc/MPhil with strong Python and ML framework experience, plus extensive work with large-scale data, Linux, containers, and HPC environments.