The Perception team at Waymo builds technology that powers the Waymo Driver. Our models allow the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We conduct 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, allowing ML practitioners like you to develop multi-modal models and techniques at scale.

You will report to our Director of Engineering in our Perception Organization.

You will:

• Develop sensor-fusion foundation models for the Waymo Driver which can run on the car and provide a temporal-spatial understanding of the surrounding environment
• Solve large-scale, multi-stage training of sensor fusion foundation models with millions of miles of driving data under limited labeling budget partnering with Waymo infrastructure teams
• Develop solutions for frequently updating the models and minimizing time-to-impact from observing to addressing an issue
• Optimize end-to-end latency from model training/update to model deployment
• Drive and accelerate collaborations between Perception teams, between Perception and AI Foundation teams, and partner with the teams working on Planning, Simulation and seek collaboration with Alphabet's research teams

You have:

• Master's degree or PhD in Computer Science, Engineering, or a related technical field
• 10+ years of experience in ML model development, and you have 4+ years experience with large-scale vision, video, or multi-modal foundation model development and their integration in end-to-end models
• 6+ years of experience in ML-driven production systems that develops models with large-scale data, training, evaluation, and deployment
• 6+ years of experience in a technical leadership role leading technical teams and setting technical directions in large ML Engineering organizations
• 3+ years of experience with computer vision models, or LLMs, or vision language models
• Proficiency in C++, Python, and modern deep learning toolkits like PyTorch or JAX
• Passion to lead engineering excellence and efficient model development through flywheel automation, while having direct technical experience in model quality development to achieve our goals

We prefer:

• Experience in multi-modal LLM pretraining and fine-tuning, and their infrastructure
• Experience in model distillation techniques and compute optimization
• Familiarity with end-to-end models and their development challenges

#LI-Hybrid