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.

Requirements

• +2 years of professional experience as a software developer
• Strong proficiency in Python, including building APIs, data-processing pipelines, and production-ready services
• Experience writing and maintaining tests using pytest and acceptance tests with Github Actions
• Experience developing frontend applications using Next.js and React
• Solid understanding of RESTful APIs and client–server architecture, including building FastAPI endpoints for data-intensive applications
• Familiarity with modern frontend tooling (TypeScript, CSS frameworks, component-based design)
• Experience working with Git and collaborative development workflows
• Comfortable working in a fast-paced environment and taking ownership of features end to end
• Ability to write clean, maintainable, and well-tested code

Nice to Haves

• Development & Infrastructure
• Usage of JupyterHub, JupyterLab & Airflow APIs
• Experience designing developer-facing tools or platforms
• Interest in building intuitive user experiences for technical users
• Experience with Docker and containerized deployments
• Familiarity with AWS (S3, EC2, ECR, Cognito)
• Knowledge of databases (SQL and/or NoSQL)
• AI / Machine Learning
• Exposure to ML/AI workflows or data science tooling
• Exposure to MLflow for model tracking and versioning
• Biological / Scientific Data Handling
• Experience with scientific, bioinformatics, or data-intensive applications including handling AnnData, single-cell RNA-seq, DNA/RNA sequences, or other omics datasets