AI Platform Engineer
The Role
We’re hiring a senior engineer to build core infrastructure and tools that connect our AI models to real-world use. You’ll work across the full stack — front-end, back-end, and ML infrastructure — to build systems that close the gap between idea and implementation for our AI and wet-lab scientists. Your work will enable faster design cycles, tighter feedback loops, and more seamless collaboration across disciplines.
This is a high-impact, hands-on role that directly supports our scientists, collaborators, and pharma partners. You’ll build APIs, dashboards, training and inference pipelines that turn frontier AI models into production-grade tools for drug design. Another focus will be accelerating scientific workflows with LLMs — building systems where AI helps propose and learn from experiments to drive faster cycles of discovery. It’s a rare opportunity to engineer this loop with real-world, large-scale experimental feedback (1 million drug designs measured every month).
See our papers for examples of our work [1][2], and their coverage in Science Magazine and Endpoints News.
Qualifications
- 5+ years of experience as a full-stack, ML infra, or platform engineer
- Experience building backend systems that serve ML models in production
- Strong frontend development skills (React, TypeScript, etc.)
- Deep fluency in Python; familiarity with cloud-native tools and containerization (Kubernetes, Docker)
- Strong product taste, sense, and ability to partner with wet-lab scientists and AI researchers
- High agency and a track record of shipping quickly with quality
What We Offer
- A fast-moving environment where you can build and ship tools that impact real drug programs
- The opportunity to shape how cutting-edge AI and LLMs are used to accelerate scientific discovery
- Access to modern ML models and wet-lab infrastructure for rapid experimentation
- A small, focused team where your engineering decisions have outsized impact
- Highly competitive salary, equity, and benefits package