Software Engineer

We’re looking for a Software Engineer who is excited about building large-scale scientific and AI workflows. You’ll report directly to the Software Engineering Lead and contribute to systems that sit at the heart of Basecamp’s research and discovery engine.

Software Engineering at Basecamp designs and operates the systems that accelerate the evaluation of biological and AI models, support high-throughput scientific analysis, integrate computation into scientific decision-making, and unlock capabilities that wouldn’t exist without strong engineering. Joining the team means helping build the internal infrastructure and tooling that drive how biology is analysed, designed, and explored across the company.

From day one, you’ll write production code, support high-throughput pipelines, and help shape core internal tools as they evolve. This role offers significant ownership and the opportunity to grow into specialised areas as the team expands.

You will

• Develop and maintain data-processing, inference, and analysis workflows used daily by scientists and ML researchers
• Contribute to large-scale, containerised pipelines deployed across HPC and Kubernetes environments
• Build internal tools (APIs, CLIs, dashboards) that support biological and machine-learning workflows
• Extend and automate orchestration using Dagster or Temporal to improve reproducibility and observability
• Work on performance, logging, monitoring, and operational reliability across distributed systems
• Collaborate with Platform Engineering on infrastructure usage, GPU scheduling, and cluster reliability
• Partner with scientists to understand biological workflows and help translate them into scalable, automated systems
• Participate in technical design discussions and code reviews, contributing ideas and improvements to the team’s engineering practices

This role gives you autonomy early, and space to help define key parts of our technical stack.

Requirements

• 1-5 years of experience (or equivalent projects) in Software, Data, ML, or Infrastructure Engineering
• Proficiency in Python and Go
• Experience with Docker, Kubernetes, and cloud-native development
• Familiarity with workflow systems (e.g., Dagster, Temporal, Airflow)
• Comfort with Linux systems and shell scripting
• Interest in large-scale data, ML workflows, or scientific computing
• A pragmatic, builder mindset - you enjoy improving processes and automating complex tasks
• Curiosity, collaboration, and readiness to work across disciplines
• 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