Software Engineer (AI)

TL;DR

Software Engineer (AI): Building and maintaining data processing, inference, and analysis workflows used by scientists and machine learning teams with an accent on large-scale, containerized pipelines running across HPC and Kubernetes environments. Focus on improving orchestration and automation to increase reproducibility and observability across workflows.

Location: Supportive and collaborative work environment based in central London, with flexibility.

Company

Fast-growing biotechnology company at the cutting edge of biological discovery, combining a multi-billion-gene dataset with advanced AI and machine learning.

What you will do

• Build and maintain data processing, inference, and analysis workflows.
• Contribute to large-scale, containerised pipelines running across HPC and Kubernetes environments.
• Develop internal tools such as APIs, CLIs, and dashboards to support scientific and machine learning workflows.
• Improve orchestration and automation to increase reproducibility and observability across workflows.
• Support performance, logging, monitoring, and reliability across distributed systems.
• Collaborate with scientists to understand research workflows and turn them into scalable, automated systems.

Requirements

• 1–5 years of commercial experience in software, data, ML, or infrastructure engineering.
• Strong experience with Python and Go in production environments.
• Hands-on experience building or working with distributed systems.
• Experience with Docker, Kubernetes, and cloud-native development.
• Familiarity with workflow orchestration tools such as Dagster, Temporal, or Airflow.
• Comfortable working with Linux systems and shell scripting.

Nice to have

• Exposure to AWS or Azure.
• Experience with observability tools (Prometheus, Grafana, Datadog).
• Familiarity with ML training or inference systems.
• Any exposure to bioinformatics, genomics, or biological data tools.

Culture & Benefits

• The chance to play a key role in a fast-moving and impactful field.
• A supportive and collaborative work environment based in central London, with flexibility and focus on development.
• Close cross-functional working with engineers, data scientists, and scientists.
• Competitive salary with equity.
• Comprehensive benefits including private medical cover, pension, generous time off, and enhanced parental support.
• Additional benefits such as childcare support, cycle to work scheme, and income protection.