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About the Role
As a Senior Scientific Software Engineer, you will translate cutting-edge scientific methods into robust, scalable software for AQEMIA's drug discovery platform. You will collaborate with physicists and ML researchers, bringing their prototypes into production and shaping the architecture and engineering standards of the scientific computing stack. This role offers a direct impact on accelerating the delivery of scientific discoveries to drug discovery programs.
Responsibilities
- Translate scientific strategies from StatMech research teams into scalable software components.
- Optimize compute-intensive code, including profiling, parallelization, and GPU acceleration, for reliable large-scale cloud execution.
- Expose physics-based calculations through clean APIs for integration into the technology platform.
- Package ML models (generative chemistry, property prediction) into versioned, reproducible, deployable components.
- Build scalable, GPU-efficient inference pipelines for ML models.
- Implement MLOps practices such as model and data versioning, experiment tracking, model registry, and monitoring.
- Orchestrate ML models and physics-based calculations into end-to-end workflows.
- Co-lead the architecture of the scientific computing stack and Python engineering standards (packaging, typing, testing, code review, documentation).
- Contribute to setting up and maintaining CI/CD pipelines and workflow orchestration (e.g., GitHub Actions, Docker, Airflow/Prefect, Kubernetes, Flyte).
- Stay updated with advances in cheminformatics.
Requirements
- MSc or PhD in computer science, applied mathematics, or a related quantitative field.
- Background in computational chemistry, molecular simulation, or statistical physics.
- 5+ years of software engineering experience.
- Strong expertise in a cheminformatics context.
- Strong Python skills and experience with RDKit or similar libraries.
- Solid software architecture skills, including designing modular, maintainable systems for multiple teams.
- Hands-on experience with CI/CD, containerization (Docker), and workflow orchestration (e.g., Airflow, Prefect, Kubernetes).
- Experience running compute-intensive workloads at scale on the cloud, including GPUs.
- Ability to collaborate closely with researchers, understand their methods, challenge prototypes, and explain engineering trade-offs.
- Good communication skills and a collaborative mindset.
Skills
- Python
- RDKit
- CI/CD
- Docker
- Airflow
- Prefect
- Kubernetes
- Cheminformatics
- GPU acceleration
- MLOps
- Model versioning
- Experiment tracking
- Model serving
Location
- Paris
- London
Work Type
- Hybrid
Experience Level
- Senior
Education Level
- MSc
- PhD
Benefits
- Visa sponsorship options for candidates in Paris
About the Company
- AQEMIA is a drug invention company focused on creating new medicines for unmet medical needs using its proprietary QEMI platform, which combines physics-based modeling, statistical mechanics, and generative AI.
- The company focuses on inventing novel molecular entities rather than refining existing ones, advancing them into proprietary programs and partnerships.
- AQEMIA has a diverse, multidisciplinary team of 80+ professionals in Paris and London, including chemists, physicists, machine learning experts, and software engineers.
- The Engineering team builds and scales the technical foundations for AQEMIA's drug discovery engine, covering data infrastructure, scientific compute systems, cloud operations, and more.
- AQEMIA has an expanding drug discovery pipeline in areas like Oncology, CNS, and Immuno-inflammation, with collaborations including a $140M Sanofi deal.
- The company is recognized as a DeepTech player, part of the French Tech 40 and France 2030.
- AQEMIA has raised $100M from leading investors.