Senior Scientific Software Engineer

The role

At AQEMIA, our research teams develop cutting-edge methods, from physics-based statistical mechanics calculations to fine-tuned machine learning models for generative chemistry and property prediction.

As a Senior Scientific Software Engineer, you’ll turn these methods into robust, scalable software that powers our drug discovery platform. You’ll sit at the intersection of science and engineering, working closely with physicists and ML researchers to understand their methods, challenge prototypes and bring them into production. You’ll also help shape the architecture and engineering standards of our scientific computing stack, so it stays modular, scalable and maintainable as we grow. This is an opportunity to have a direct impact on how quickly and reliably our science reaches real drug discovery programs.

Responsibilities

• Translate scientific strategies from our StatMech research teams into software components that run at scale.

• Optimize compute-intensive code (profiling, parallelization, GPU acceleration) and run it reliably at scale on our cloud infrastructure.

• Expose physics-based calculations through clean APIs that integrate into our technology platform.

• Package ML models fine-tuned by our AI research teams (generative chemistry, property prediction, etc.) into versioned, reproducible, deployable components, and build scalable, GPU-efficient inference pipelines.

• Implement MLOps practices, including 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 our scientific computing stack and our Python engineering standards: packaging, typing, testing, code review and documentation.

• Contribute to setting up and maintaining CI/CD pipelines and workflow orchestration (e.g. GitHub Actions, Docker, Airflow/Prefect, Kubernetes, Flyte), and stay up to date with advances in cheminformatics.

Qualifications

• MSc or PhD in computer science, applied mathematics or a related quantitative field, with a background in computational chemistry, molecular simulation or statistical physics.

• 5+ years of software engineering experience, with strong expertise in a cheminformatics context.

• Strong Python skills and experience with RDKit or similar libraries.

• Solid software architecture skills: designing modular, maintainable systems used by several 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 work closely with researchers (understanding their methods, challenging prototypes and explaining engineering trade-offs), with good communication skills and a collaborative mindset.

Why Join Us ?

At AQEMIA, we work for a mission: joining us means having your own impact on changing the way drugs are discovered, and helping to shape the direction of our fast-growing company and team.

Expanding Drug Discovery Pipeline: Focused on critical therapeutic areas like Oncology, CNS, Immuno-inflammation... with in vivo proof of concept/patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal.

World-Class Interdisciplinary Team: work alongside exceptional talent at the intersection of technology and life sciences. Our teams combine deep expertise in AI, physics-based modeling, biology, and medicinal chemistry to push the boundaries of innovation.

DeepTech Recognition: AQEMIA is proud to be part of the French Tech 40 and France 2030, highlighting our role as a key player in Europe’s DeepTech ecosystem.

Prime Location with Flexibility: Our offices are located in the heart of Paris and London (King’s Cross), with flexible work arrangements including up to two remote days per week.

Strong Financial Backing: $100M raised from leading European and International investors

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.