About us
At Basecamp Research, we explore the world’s unseen biodiversity to unlock nature-designed solutions for biotechnology’s hardest challenges. Through expeditions, partnerships, and large-scale sequencing efforts, we’ve built one of the world’s most unique metagenomic datasets - powering next-generation protein and genomics foundation models.
Our work sits at the intersection of machine learning, synthetic biology, large-scale data, and exploratory science, with applications in therapeutics, materials, industrial enzymes, and beyond. We’re an inclusive, interdisciplinary environment where biologists, ML researchers, software engineers, and field scientists work side-by-side to push the boundaries of what’s possible.
About the job
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
This role gives you autonomy early, and space to help define key parts of our technical stack.
About you
You don’t need a biology background, just curiosity, strong fundamentals, and eagerness to learn.
You bring:
- 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
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
If you're excited about the space but don’t tick all the boxes, we still encourage you to apply.
What we can offer in return
- The opportunity to be a key member in an exciting, dynamic, and fast-moving field.
- A fun, flexible, and supportive work environment in the centre of London, and an emphasis on collaboration and personal development.
- Highly collaborative culture, we always work cross team and cross function, with engineers, data scientists, and biologists working directly together to tackle complex issues.
- Competitive compensation including equity
Apply for the job
Do you want to join our team as our new Software Engineer? Then we'd love to hear about you!
