Software Engineer - Research Data Platform

Role overview This mid-to-senior individual contributor role focuses on building the data backbone for an AI foundation model targeting biology. You will design and scale the storage and access layers that make massive, complex biological datasets usable by researchers, product engineers, and AI agents, working at the intersection of life sciences and machine learning infrastructure.

Responsibilities - Architect and maintain scalable data schemas and storage solutions tuned for high-performance AI workloads over biological data. - Benchmark, profile, and extend distributed storage using chunking, compression, parallelization, and custom optimizations. - Build clean, typed, well-documented APIs that allow researchers, engineers, and AI agents to query and extend the platform programmatically. - Monitor and tune database queries, read/write paths, pipeline bottlenecks, and cloud infrastructure costs. - Collaborate with platform engineers on data validation, testing, versioning, and access control to ensure governance and security. - Partner with researchers and product engineers to scope needs, align on priorities, and own projects end-to-end.

Requirements - Production-level Python expertise with a focus on clean, readable, maintainable code. - Hands-on experience with modern Python data tooling, including Pydantic, SQLAlchemy, Alembic, object storage abstractions, and FastAPI or similar frameworks. - Strong knowledge of relational databases such as PostgreSQL, including schema design, indexing strategies, and query optimization. - Experience designing scalable, structured storage systems for large and complex datasets. - Comfort working in a fast-paced, multidisciplinary team spanning research and engineering. - Independent, curious, detail-oriented mindset with strong collaboration skills.

Benefits and work setup - Remote-friendly position with headquarters in Paris; the role can be performed remotely outside of Paris. - Competitive salary plus equity package. - Mission-driven environment focused on applying AI to accelerate discovery in biology. - Flexible work arrangements.