Software Developer - Biology
Helical is building the in-silico labs for biology
Drug discovery still relies on wet labs: slow, expensive, and constrained by physical trial-and-error. Helical is changing that.
We build the application layer that makes Bio Foundation Models usable in real-world drug discovery, enabling pharma and biotech teams to run millions of virtual experiments in days, not years. Today, leading global pharma companies already use Helical, and we’re at the start of a highly ambitious growth journey.
We’re a founder-led, talent-dense team building a category-defining company from Europe. We care deeply about the quality of our work, move fast, and expect ownership. If you’re excited by complexity, real responsibility, and shaping how a company actually operates as it scales, you’ll feel at home here.
About the Role
We are looking for a Software Developer with a strong background in computational biology or bioinformatics to join our core product development team.
This unique role bridges cutting-edge biological data science and software engineering, helping bring novel bio foundation models into production and optimize workflows for biological data processing and model execution.
The ideal candidate is passionate about biology, enjoys coding and problem solving at scale, and is eager to collaborate across teams of ML scientists, backend engineers, and biologists.
Responsibilities
- Design, implement, and maintain scalable pipelines for biological data processing and analysis
- Integrate and optimize Bio Foundation Models for production use, collaborating with ML researchers
- Develop tools and services for data visualization, annotation, and quality control of biological datasets
- Collaborate closely with AI infrastructure and software engineers to improve workflow reliability and scalability
- Contribute to the architecture and implementation of backend services and APIs supporting biological workflows
Requirements
- MSc or PhD in Biology, Computational Biology, Bioinformatics, or a closely related life sciences field — you studied the science
- 2+ years of professional software development experience — you've shipped production code, not just notebooks
- Python — strong, production-grade foundations; comfortable with package structure, clean code patterns, and debugging across complex codebases
- Single-cell analysis — hands-on experience with the modern single-cell stack: AnnData, scanpy, scib, scipy, and related tools
- Biological reasoning — you can look at a set of model predictions and assess whether they make biological sense; you understand experimental design, perturbation biology, and what "evidence" means in a discovery context
- Data fluency — comfortable working with large biological datasets, understanding file formats (h5ad, csv, parquet), and writing efficient data processing code
- Familiarity with Git workflows and collaborative development practices
Nice to Haves
- Exposure to bio foundation models — you've worked with or fine-tuned models like scGPT, Geneformer, scVI, or similar
- Experience with pytest and test-driven development practices
- Familiarity with cloud development (AWS, GCP, or Azure) — running workloads beyond your local machine
- Experience with CI/CD pipelines and automated deployment workflows
- Working knowledge of Docker and containerised development environments
- Experience in pharma or biotech — you understand the compliance and validation expectations that come with the territory
- Proven product already in use with top pharma
- Opportunity to shape a category-defining company at an inflection point
- High ownership, direct impact, and close collaboration with founders
- Competitive Salary, Equity and Benefits
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