Scientific Software Engineer - Computational Chemistry
Paris / London
Engineering – DD Team /
Full-time contract /
Hybrid
About Aqemia
Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI.
Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data.
Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis.
We’ve already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization.
We’re a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what’s possible in early-stage drug discovery.
The Role
As a Scientific Software Engineer you will contribute directly to building the product supporting drug hunters daily activities and accelerating Aqemia’s drug discovery programs.
You will work at the intersection of cheminformatics, software engineering, and drug discovery, designing and implementing tools that serve scientists and guide compound design decisions.
This is a key technical role with strong cross-functional impact across medicinal chemistry, physics modeling, and AI teams.
What you’ll do
- Collaborate with medicinal chemists in DD programs, understand and translate their needs, and support them in adopting Aqemia’s technology
- Design and build DD workflows and pipelines to accelerate discovery programs
- Develop the core internal tool of Aqemia, essential to Drug Hunters’ daily operations
- Support Drug Hunters in DD programs, working closely with them to understand their scientific needs and help them adopt Aqemia’s technology
- Design and implement end-to-end DD workflows and pipelines to accelerate hit identification and optimization
- Build the core internal tool of Aqemia, central to daily DD activities, enabling data analysis, decision tracking, computation scheduling, and project management
- Collaborate with AI scientists, cheminformaticians, and engineers to ensure smooth integration of scientific models into product workflows
- Contribute to the usability and robustness of the platform, through clear UI, reliable backend services, and strong technical practices
- Promote best practices in collaborative development, reproducibility, and data traceability across the team
What we’re looking for
- 2 - 4 years of experience in cheminformatics or computational chemistry, ideally in a drug discovery context
- Strong programming skills in Python, experience with RDKit or similar toolkits
- Familiarity with molecular descriptors, compound clustering, virtual screening, and property prediction
- Good understanding of medicinal chemistry principles and compound design strategies
- Experience working with data in SQL and/or NoSQL databases
- Ability to communicate effectively with interdisciplinary teams and translate scientific needs into technical solutions
Preferred mindset
- You’re excited to build products that directly impact drug discovery projects
- You enjoy solving complex scientific problems with clean, scalable code
- You thrive in a collaborative, fast-paced environment
- You care about clarity, impact, and continuous improvement
Why Join Us
At Aqemia, engineers don’t just build software, they help discover real drugs.You’ll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery.
DeepTech Mission : Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models
Real-World Impact : Every feature shipped helps scientists prioritize molecules and design better candidates, faster
Modern Stack & Challenges : Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale
High Ownership, High Impact : Engineers contribute to architecture, tooling, and scientific decision-making
Interdisciplinary Team : Collaborate with chemists, physicists, ML researchers, and product teams
Prime Locations : Central Paris or London offices, with 2 remote days/week
Strategic Traction : Backed by $100M in funding and a $140M partnership with Sanofi
Join us if you’re excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.
