Sr Staff Tech Lead, Machine Learning Engineer, Perception

The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.

In this hybrid role, you'll report to a Senior Staff Technical Lead Manager.

You will:

• Set the long-term technical roadmap for next-generation multi-modal perception architectures, driving paradigm shifts in multi-task learning, spatial-temporal modeling, and scene representation.
• Architect unified, scalable representations combining diverse sensor modalities across heterogeneous sensor suites.
• Lead cross-functional initiatives across Perception and Planner and partner with hardware and infrastructure teams to optimize foundational architectures for onboard requirements.
• Mentor ML engineers and foster an engineering culture of rapid prototyping and rigorous benchmarking.

You have:

• BS or MS in Computer Science, Robotics, Machine Learning, or equivalent practical experience.
• 8+ years of industry experience in Machine Learning, AI or Computer Vision.
• Proven track record of architecting and shipping large-scale, production-grade machine learning models.
• Expert proficiency in Python, C++, and modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).
• Demonstrated experience leading large technical initiatives as a Tech Lead across cross-functional teams.

We prefer:

• PhD with a publication record at top-tier venues.
• Strong industrial experience multi-modal foundation models, 3D perception, or end-to-end autonomous driving systems.
• Experience designing modular, sensor-agnostic perception frameworks that scale across diverse configurations.