The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
About the Roche R&D Autonomous Lab Accelerator
Roche R&D Autonomous Lab Accelerator is building AI-native scientific laboratories, bringing cutting-edge physical AI, lab automation, and foundation models together for closed-loop, autonomous "Lab-in-the-Loop" (LitL) systems. Through autonomous labs, Roche will drive superior R&D outcomes and systematically increase the speed of research and success of drug discovery.
The Opportunity
As the Global Head of Platform Technology Development, you will translate our multi-year AI-native autonomous lab vision into rigorous technology platform capabilities and deliverables. You will determine our internal scientific R&D workflow needs, identify technology gaps, and build fit-for-purpose physical capabilities across laboratory automation systems and robotics.
Your core mission is to lead core technology platform development, ensuring interoperability, robust architectural design, and scalable autonomous lab systems for Roche R&D needs that span Genentech Research and Early Development (gRED), Pharma Research and Early Development (pRED), Diagnostics (DIA), and Pharma Technical Operations (PT).
In this role, you will:
Platform technology development
Implement advanced automation platform technologies for prioritized use cases across the Accelerator program.
Lead the development and integration of fit-for-purpose platform technologies (i.e. bespoke microwell / microfluidics hw /sw systems) for Roche R&D autonomous labs.
Map and track the external landscape: robotics and physical AI companies, instrument and liquid handling vendors, cloud and autonomous labs, and industry players now building their own autonomous-lab platforms.
Lead technical diligence on partnerships and acquisitions; scope and shape co-development and commercial agreements.
Co-own data standards with the lab automation software lead, and run architecture reviews / technical diligence that new automation purchases and partnerships must pass.
Physical AI & Digital Twins
Digital Twin Architecture: Direct the development of high-fidelity 3D digital twin models of the autonomous laboratory. Ensure 1:1 synchronization between physical lab telemetry and the virtual environment to enable predictive system modeling, spatial optimization, and real-time fleet monitoring.
Sim-to-Real (Sim2Real) Pipeline Execution: Oversee advanced robotics simulation efforts (leveraging environments like NVIDIA Isaac Sim, or equivalent). Build robust synthetic data generation pipelines to train AI agents in physics-accurate virtual labs before safely deploying them to physical R&D laboratories.
Edge AI & Low-Latency Inference: oversee the deployment and optimization of compact vision and VLA models at the edge to establish millisecond-latency monitoring of the physical lab state for mission-critical operations.
Edge Computing Optimization: Demonstrated experience leading the deployment and optimization of AI inference on resource-constrained edge hardware (e.g., NVIDIA Jetson, TensorRT quantization) to support real-time physical control loops and low-latency sensor networks.
Simulation & Digital Twin Experience: Experience overseeing teams working with 3D robotics simulation, synthetic data generation, and closing the sim-to-real transfer gap. Familiarity with industrial digital twin concepts and their application to complex operational environments.
Advanced Robotics Background: Technical familiarity with robotic kinematics, computer vision (segmentation, pose estimation), and modern ML techniques for continuous control and robotic manipulation.
Build the Team and Represent the Function
Hire and lead the automation platform technologies, robotics and…