Genentech
Senior Physical AI & Robotics Scientist - Lab Automation
South San Francisco · Senior
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About the role
- Advances in AI, data, and computational sciences are transforming drug discovery and development.
- Apply system identification, domain randomization, and sim-to-real tuning to ensure simulation-trained control policies execute predictably on physical hardware.
- Fine-tune multimodal Vision AI models (VLMs, NVIDIA Cosmos) using synthetic failure datasets (Isaac Sim) for real-time detection of lab anomaly modes (spills, bubbles, dropped microplates, tilted lids, tip-pick misses).
Responsibilities
- Build multi-physics simulation environments (NVIDIA Isaac Sim/Lab, Newton Engine) to model robot-labware interactions, evaluate LLM-generated execution plans inside digital twins before deployment, and train policy recovery models.
- Optimize low-latency inference with TensorRT on NVIDIA Jetson (Thor/Orin) edge hardware, combining visual servoing and closed-loop feedback control so systems self-correct without halting master workflows.
- It's what drives us to innovate.
- Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact.
- building fully autonomous, self-healing laboratories for lights-out drug discovery.
Requirements
- Passionate builder with a proven track record of taking real-world robotic manipulation and sim-to-real systems beyond demonstrations into sustained operation.
- Proficiency with visual servoing, closed-loop controllers, and hardware API integration (gRPC, SiLA 2, vendor SDKs).
- Experience working with high-throughput lab automation hardware, manipulators, or liquid handlers (e.g., Hamilton, Tecan, Precise Automation, UR arms).
- Hands-on experience with OpenUSD scene graphs, custom USD schemas, or NVIDIA Omniverse workflows.
Nice to have
- Preferred but not required
Compensation
- Hands-on experience with OpenUSD scene graphs, custom USD schemas, or NVIDIA Omniverse workflows.
Benefits
- To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come.
Equal opportunity
- equal opportunity employer.
- If you have a disability and need an accommodation in relation to the online
This listing is sourced directly from Genentech's careers page and normalized into a canonical job model.