Forward Deployed Data Engineer for Frontier AI & Biology

The Ellison Institute Of Technology (eit); Oxford; Hybrid; GBP 85,000 - 120,000; Full time

Benefits offered by this job

Salary dependent on experience

Travel allowance

Bonus

25 days annual leave + bank holidays +

Private Medical Insurance

Job summary

The Ellison Institute Of Technology (EIT) invites applications for a Forward Deployed Engineer within the Scientific Compute and Data Team in the UK. You will collaborate with scientists and engineers to craft robust data pipelines, ingest diverse bio datasets, and deploy code in research environments using containers like Docker.

You will scale workloads on distributed cloud resources and advocate for reproducible data practices across projects.

Qualifications

• Strong programming experience in Python.
• Experience with data storage and manipulation in relational systems.
• Experience with cloud compute platforms and varied Linux environments.
• Experience preparing data for ML and bioinformatics domain knowledge preferred.

Responsibilities

• Partner with scientists and engineers to deliver robust, reproducible data pipelines.
• Own ingestion, storage, curation, and transformation of diverse biological datasets and formats.
• Package and deploy code in research environments using containers (e.g. Docker).
• Scale processing across distributed cloud warehouses/storage via container orchestration (e.g. Kubernetes).
• Promote data engineering best practices: reproducibility, version control, schema design and lineage.
• End-to-end ownership from low-level performance to user interfaces.
• Collaborate on projects across genomics, proteomics, and bioinformatics domains.

Job description

The Ellison Institute Of Technology (EIT) invites applications for a Forward Deployed Engineer within the Scientific Compute and Data Team in the UK. You will collaborate with scientists and engineers to craft robust data pipelines, ingest diverse bio datasets, and deploy code in research environments using containers like Docker.

You will scale workloads on distributed cloud resources and advocate for reproducible data practices across projects.