Senior Scientific Software Engineer – Python & Machine Learning

Our client, a pioneer in the biotechnology sector, is seeking a professional to bridge the gap between research code and production software. The role involves evolving a scientific Python package to ensure reliability and scalability for biological innovation projects. The focus lies on transforming experimental workflows into robust, maintainable software used by researchers across the organization.

• Design and evolve public Python APIs while maintaining stable internal structures and backward compatibility.
• Translate biological research code and experimental workflows into reusable and scalable software capabilities.
• Deploy machine learning models using frameworks like PyTorch and TensorFlow while managing complex dependency conflicts.
• Implement multi-level testing strategies including unit, integration, and numerical regression tests against scientific fixtures.
• Manage production CI/CD pipelines incorporating linting, type checking, and platform compatibility checks.
• Oversee release management using semantic versioning, deprecation strategies, and comprehensive documentation.
• Optimize computationally intensive workflows through profiling, benchmarking, and containerization in HPC environments.

• You have 8+ years of software engineering with Python, focusing on API design, library development, and modern packaging like Poetry, uv, or PDM.
• You possess 5+ years experience training and deploying models with PyTorch or TensorFlow in production environments.
• You bring 5+ years designing CI/CD pipelines including linting, type checking with mypy, and automated testing.
• You have 5+ years with Git discipline, semantic versioning, and managing complex merge conflicts in scientific codebases.
• You bring experience translating biological concepts and experimental workflows into software tools.
• You're proactive and focused on code correctness and numerical accuracy.
• You are fluent in English.

Nice to Haves

• Experience with biological foundation models, fine-tuning, and sequence models for RNA or proteins.
• Knowledge of multi-framework architecture using lazy imports and abstract backend patterns.
• Hands-on experience with HPC environments, SLURM, Singularity, and Apptainer.
• Understanding of genetic algorithms and core bioinformatics data formats.

• Start date: ASAP
• Duration: Until December with a possible 1-year extension.
• Work regime: Full-time
• Location: Remote
• Working model: Full remote
• Contract: open to both permanent employees and freelancers