Design, build, integrate, and improve bespoke hardware and commercial equipment for automated chemistry workflows. Responsibilities include developing dispensing, handling, heating, cooling, sampling, and analysis systems; designing parts; assembling prototypes; writing hardware-control software; debugging in the laboratory; and taking systems from concept through reliable deployment. The role requires close collaboration with chemists and hands-on ownership in a fast-moving, resource-constrained environment.

Train and deploy machine learning models for chemistry applications, including reaction planning, outcome prediction, material-cost estimation, and mass-spectra prediction. Responsibilities span data acquisition, model development, training infrastructure, parallelism, quantization, inference, and integration with robotic laboratory workflows. The role requires strong empirical machine learning fundamentals, cross-disciplinary collaboration, rapid experimentation, and comfort working across the full ML stack in an in-person chemistry lab environment.