Forward Deployed Data Engineer for Scientific AI & Robotics

Ellison Institute of Technology; Oxford; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Travel allowance

Pension 7.5%

Life Assurance

Income Protection

Private Medical Insurance

Employee discounts

Cycle to Work

Neurodiversity support

Coaching & Therapy

Job summary

Ellison Institute of Technology (EIT) in the UK seeks a Forward Deployed Engineer for our Scientific Compute and Data Team. You will work alongside scientists and engineers on frontier AI, robotics, and genomics, turning research questions into scalable data pipelines and reliable ML-ready datasets.

This hands-on role emphasizes collaboration, clear communication, and end-to-end ownership of data infrastructure, from ingestion to model-ready outputs, with chance to influence diverse research

Qualifications

• Strong programming experience in Python with focus on code quality.
• Experience with data storage, relational systems, indexing, and scalability.
• Experience on cloud compute platforms and varied Linux environments.
• Experience at scale with distributed data systems.
• Familiarity with data engineering best practices: reproducibility, version-control, schema design.

Responsibilities

• Partner with scientists and engineers to deliver robust data pipelines.
• Ingest, store, curate, and transform diverse biological datasets.
• Package and deploy code in research environments using containers.
• Scale processing across distributed cloud warehouses and GPUs.
• Contribute to maintainable, well-tested, scalable systems.
• Collaborate across disciplines and communicate clearly.

Skills

Python programming

Data storage & manipulation

Cloud compute platforms

Linux environments

Distributed data systems

End-to-end ownership

Tools

Docker

Nextflow

Spark

Ray

Job description

Ellison Institute of Technology (EIT) in the UK seeks a Forward Deployed Engineer for our Scientific Compute and Data Team. You will work alongside scientists and engineers on frontier AI, robotics, and genomics, turning research questions into scalable data pipelines and reliable ML-ready datasets.

This hands-on role emphasizes collaboration, clear communication, and end-to-end ownership of data infrastructure, from ingestion to model-ready outputs, with chance to influence diverse research