Senior Scientific Developer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and sustain scientific software for drug discovery, including docking, free-energy perturbation (FEP), molecular dynamics, cheminformatics, and associated computational biology workflows.

• Create and enhance the Deep Origin Python SDK and scientific APIs that researchers utilize to execute, monitor, and evaluate platform workflows.

• Develop and support Julia-based simulation and analysis packages for molecular systems, covering aspects such as system preparation, MD/FEP protocols, and post-processing.

• Author and manage workflow definitions (Argo Workflows) and serverless scientific services (Knative) that coordinate multi-step computational pipelines on Kubernetes.

• Package scientific tools as reproducible, containerized functions, ensuring clear input/output contracts, validation, and integration tests.

• Convert domain requirements from medicinal chemistry and computational biology into robust and scalable technical implementations.

• Collaborate with platform engineering, product, and scientific teams to embed scientific tools into our multi-tenant cloud platform.

• Maintain scientific code quality through testing, documentation, benchmarking, and meticulous management of edge cases in real-world molecular datasets.

• Troubleshoot and resolve issues across the entire stack — from numerical methods and force-field behavior to workflow failures in production.

• Contribute to engineering best practices, including code reviews, CI/CD, observability, and operational runbooks for long-running scientific tasks.

• Mentor colleagues and elevate the standards for scientific software engineering within the organization.

⛳️ Requirements

• MSc or PhD in chemistry, chemical biology, bioinformatics, computational chemistry, or a closely related discipline — or equivalent industry experience with a strong scientific background.

• Extensive domain knowledge in at least one of the following: medicinal chemistry, cheminformatics, structural biology, molecular simulation, or computational drug discovery.

• Proficient in **Python** — you write clean, tested, production-quality code and feel at ease building libraries and APIs, not merely notebooks and scripts. Specifically, this entails:

• - You have authored and maintained an installable Python package; publishing to PyPI is a significant advantage.

• - You work with modern packaging and environments (`uv`, `conda`, or `pixi`).

• - Linting and type checking are integral to your standard workflow (`ruff`, `ty`).

• - You have utilized Marimo (or comparable reactive/reproducible notebook tools) for scientific exploration, demonstrations, or documentation.

• Strong **Docker** competencies — you are adept at containerizing scientific Python code for production use, not just executing pre-built images. This includes:

• - Knowledge of how to containerize Python scripts, packages, and dependencies into stable images.

• - Ability to write multi-stage Dockerfiles for complex build pipelines.

• - Expertise in optimizing image size (layer caching, slim base images, build-arg hygiene, and maintaining lean runtime images).

• Experience in implementing scientific algorithms and workflows from end to end, transitioning from prototypes to deployed, maintainable software.

• Familiarity with AI-assisted development — you fluently use tools like Claude Code and Cursor, discerning where they expedite your work and where scientific accuracy necessitates human oversight.

• Strong foundation in software engineering principles: testing, version control, debugging, and crafting clear interfaces for intricate scientific data.

• Capability to read scientific literature and translate methods into functioning implementations.

• Methodical problem-solving skills with a strong sense of accountability.

• Ability to perform both independently and collaboratively in a dynamic startup environment.

• **Preferred:**

• Substantial experience with Julia, particularly in scientific computing, molecular dynamics, or high-performance numerical tasks.

• Practical experience with Kubernetes and cloud-native deployment strategies.

• Familiarity with Argo Workflows (or similar workflow orchestration platforms) and Knative (or comparable serverless/container platforms).

• Understanding of molecular simulation ecosystems: force fields, system preparation, alchemical free-energy methods, or MD analysis pipelines.

🏝️ Benefits

• **What we offer**

• - Opportunity to influence the future of health, longevity, and our capability to simulate life.

• - Competitive compensation package with significant equity.

• - Comprehensive health, dental, and vision coverage.

• - Annual team gatherings and company events.

• - Complimentary lunch, snacks, beverages, and access to an onsite gym (for in-office employees).