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