Staff TLM, Perception, Sensor Pipelines

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

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.

Perception has many different vertical pipelines solving different real-world problems beyond just object detection and understanding, the Sensor Pipelines team works on a diverse portfolio of problems such as weather, road surface understanding, visibility, and detection of exceptional events around the car. These pipelines often have a strong aspect of sensing technology, but also stretch the entire Perception stack and interfacing with planning as well.

In this hybrid role you will report to a Senior Engineering Manager and manage and grow a team of engineers working on Perception ML pipelines.

You will:

• Manage a team of Software engineers & Machine Learning engineers to estimate the weather conditions around a vehicle.
• Develop Machine Learning models that work well in low-data regimes (few-shot learning etc).
• Work with downstream customer teams to set requirements, align with their product roadmaps, etc.
• Responsible for people development and hiring for a growing team, build resilient and high performing teams.
• Drive the team to design excellent ML solutions in collaboration with TLs in the team, and foster an atmosphere of high achievement.
• Represent the team in the larger Perception and Onboard group, including collaborating with other leads around on staffing and planning. Define team OKRs, develop believable plans to achieve the OKRs, and drive the roadmap execution.
• Make project staffing decisions, technical decisions, drive escalations; ultimately accountable for delivering projects.

You have:

• Bachelor’s in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
• Experience managing software engineers, and managers of software engineers.
• Both general previous experience in ML, as well as hands-on experience managing and leading ML projects.
• 8+ years of industry experience

We prefer:

• MS or PhD in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
• Previous experience working on or with sensing hardware
• Previous experience working in the self-driving or robotics space
• Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI.

This role follows a hybrid work schedule and reports to a Senior Engineering Manager.

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.