Accelerating R&D to untangle the complexity of life
Senior Scientific Developer
Location
United States
Posted
1 day ago
Salary
0
Seniority
Senior
Job Description
Senior Scientific Developer
Deep Origin
• Design, implement, and maintain scientific software for drug discovery: docking, free-energy perturbation (FEP), molecular dynamics, cheminformatics, and related computational biology workflows. • Build and evolve the Deep Origin Python SDK and scientific APIs that scientists use to run, monitor, and analyze platform workflows. • Develop and maintain Julia-based simulation and analysis packages for molecular systems (e.g., system preparation, MD/FEP protocols, post-processing). • Author and operate workflow definitions (Argo Workflows) and serverless scientific services (Knative) that orchestrate multi-step computational pipelines on Kubernetes. • Package scientific tools as reproducible, containerized functions with clear input/output contracts, validation, and integration tests. • Translate domain requirements from medicinal chemistry and computational biology into robust, scalable technical implementations. • Collaborate with platform engineering, product, and science teams to integrate scientific tools into our multi-tenant cloud platform. • Ensure scientific code quality through testing, documentation, benchmarking, and careful handling of edge cases in real-world molecular datasets. • Debug and resolve issues across the full stack — from numerical methods and force-field behavior to workflow failures in production. • Contribute to engineering best practices: code review, CI/CD, observability, and operational runbooks for long-running scientific jobs. • Mentor teammates and help raise the bar for scientific software engineering across the organization.
Job Requirements
- MSc or PhD in chemistry, chemical biology, bioinformatics, computational chemistry, or a closely related field — or equivalent industry experience with a strong scientific track record.
- Deep domain knowledge in at least one of: medicinal chemistry, cheminformatics, structural biology, molecular simulation, or computational drug discovery.
- Excellent **Python** skills — you write clean, tested, production-quality code and are comfortable building libraries and APIs, not just notebooks and scripts. In practice, that means:
- You have authored and maintained an installable Python package; publishing to PyPI is a strong plus.
- You work with modern packaging and environments (`uv`, `conda`, or `pixi`).
- Linting and type checking are part of your default workflow (`ruff`, `ty`).
- You have used Marimo (or similar reactive/reproducible notebook tools) for scientific exploration, demos, or documentation.
- Strong **Docker** skills — you are comfortable containerizing scientific Python code for production, not just running pre-built images. In practice, that means:
- You know how to containerize Python scripts, packages, and dependencies into reliable images.
- You can write multi-stage Dockerfiles for complex build pipelines.
- You know how to trim image size (layer caching, slim base images, build-arg hygiene, and keeping runtime images lean).
- Experience implementing scientific algorithms and workflows end to end, from prototype to deployed, maintainable software.
- AI-assisted development — you use tools like Claude Code and Cursor fluently, and you have judgment about where they accelerate you and where scientific correctness demands human review.
- Strong fundamentals in software engineering: testing, version control, debugging, and designing clear interfaces for complex scientific data.
- Ability to read scientific literature and translate methods into working implementations.
- Systematic problem-solving approach with a strong sense of ownership.
- Ability to work both independently and collaboratively in a fast-moving startup.
- Preferred: **
- Substantial experience with Julia, especially for scientific computing, molecular dynamics, or high-performance numerical work.
- Hands-on experience with Kubernetes and cloud-native deployment patterns.
- Experience with Argo Workflows (or similar workflow orchestration) and Knative (or similar serverless/container platforms).
- Familiarity with molecular simulation ecosystems: force fields, system preparation, alchemical free-energy methods, or MD analysis pipelines.
Benefits
- What we offer**
- Opportunity to shape the future of health, longevity, and our ability to simulate life.
- Competitive compensation package with meaningful equity.
- Comprehensive health, dental, and vision coverage.
- Annual team gatherings and company events.
- Free lunch, snacks, beverages, and onsite gym access (for in-office employees).
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