Senior Scientific Developer

🕒 Julho 9

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Deep Origin

SiteLinkedInTodas as Vagas

11 - 50 funcionários

🏥 Saúde

💼 Consultoria

📦 Logística

Healthcare • Consulting • Logistics

A Deep Origin é uma empresa de ponta focada em acelerar a pesquisa e o desenvolvimento nas ciências da vida por meio de sua plataforma e de ferramentas inovadoras. Ela oferece um conjunto de ferramentas de simulação molecular e uma plataforma de P&D que aproveitam o poder da inteligência artificial e de uma gestão de dados integrada. As soluções da Deep Origin são projetadas para ajudar cientistas a enfrentar desafios complexos, biológicos e relacionados a doenças, fornecendo ferramentas para análise de dados, simulação molecular e descoberta de fármacos. A empresa busca revolucionar a biologia computacional e simular processos biológicos para apoiar a descoberta de novas terapias e a compreensão de doenças. As ofertas da Deep Origin incluem assistentes de análise com IA, workstations de alto desempenho e recursos de triagem virtual de fármacos, tornando-a uma poderosa aliada para pesquisa e desenvolvimento científicos interdisciplinares.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• **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).