Artificial Intelligence Engineer

Expectations:

Collaborate closely with teams in ML research, drug design, and data engineering to design, train, and evaluate cutting-edge machine learning models at scale
Help build a state-of-the-art research environment for ML-driven drug discovery, supported by robust, scalable software and libraries
Create tools and infrastructure that enable large-scale ML experimentation across thousands of accelerators
Optimize model efficiency, scalability, and resilience for real-world use within our computational platform
Partner with scientific experts to develop innovative tools that advance drug discovery, taking ideas from rapid prototypes through to production-ready systems
Work iteratively with domain experts to refine features and incorporate user feedback into development

Requirements:

Proven track record of building and scaling advanced machine learning models
Strong programming skills, with significant experience in Python and at least one other major language
Hands-on experience with modern ML frameworks such as JAX, PyTorch, or TensorFlow
End-to-end familiarity with the ML lifecycle, from research through to deployment
Experience collaborating with research and product teams to prototype and operationalize ML models
Solid background in software engineering, including system design and architecture
Strong grasp of ML theory, practical applications, algorithms, and data structures
M.S OR B.A in Computer Science, Engineering, or a related technical discipline

Nice to have:

Experience in life sciences, particularly chemistry and biology
Experience working with biomedical or pharmaceutical datasets
Understanding of the drug discovery process and industry context
Background in developing user-facing production software