The Position
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 simulations engineering function within the Accelerator.
- Represent Roche externally (SLAS, consortia, standards bodies, partner boards) as a credible voice on lab-in-the-loop.
Who you are:
- Education: MS/PhD in Engineering (Mechanical, Electrical, Robotics), Computer Science, Bioengineering, or equivalent practical experience.
- Industry Leadership: 15+ years of experience in laboratory automation, high-throughput experimentation, or autonomous platforms, with significant leadership and team-building experience in Biopharma or Techbio.
- Robotics & Tech Stack Expertise: Demonstrated experience driving the shift from hard-coded robotic systems to agentic programmability and flexible control. Familiarity with integration protocols (Python, gRPC, REST), robotic simulation environments, and closing execution loops with foundation models/AI systems.
- Physical AI / ML Expertise: Demonstrated understanding of the latest advancements in robotics foundation models (e.g., VLA architectures, spatial reasoning VLMs) and the practical challenges of deploying them on physical hardware in a lab setting.
- Regulated Environments: Experience transitioning hardware and software platforms into GxP, and regulated environment use.
- Cross-Functional Acumen: Proven ability to collaborate with scientific product managers, software engineers, and AI researchers to translate complex biological/chemical workflows into robust hardware specifications.
Relocation benefits are available for this opportunity
The expected salary range for this position based on the primary location of San Francisco is $261,500 - 485,700 of hiring range. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
