Hiring.Camp

Senior Staff Technical Lead Manager, Perception Optimization

Waymo

·

Dec 26, 2025

Workplace
Hybrid
Type
Full-time
Department
IT
Seniority
Staff
Experience
8+ years
Education
PhD

Description

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.

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.

The Sensor Foundations Team’s purpose is to provide cleaned-up sensor data through highly optimized APIs to Perception models, to abstract sensor hardware differences where possible, and to provide low-level Perception signals either through algorithms or machine learning. Projects on our team typically require a diverse skill set, including robotics, system integration, code optimization, and machine learning. We have a good understanding of the hardware (both sensors and compute) and the overall Perception system.

The Optimization sub-team uses our know-how of CPUs, GPUs, and clever algorithms to process Waymo's sensor data super-fast and feed it to the Perception ML models. We specialize in low-level understanding of compute hardware, and we apply that knowledge wherever we can, throughout the whole stack. We are looking for a Tech-Lead Manager with a CPU, GPU, or system-level optimization background to lead this small team of Software Engineers. Depending on your prior experience, you may also be responsible for system-level optimization and be a steward of our compute resources.

This role follows a hybrid work schedule and reports to the TLM of the Sensor Foundations team.

You will:

  • Lead a small team of optimization experts 
  • Identify system-level optimization opportunities
  • Optimize existing CPU code
  • Write and review CUDA code
  • Collaborate with ML practitioners to understand their input-processing needs.
  • Be a steward of our compute resources

You have:

  • B.Sc in Computer Science, Mathematics or a related field
  • 8+ years of industry experience
  • Strong C++ programming skills
  • Experience with optimizing CPU or GPU code (ideally both)
  • Experience with system-level optimization

We prefer:

  • M.Sc or PhD in Computer Science, Mathematics or a related field
  • Experience with compiler technology.
  • Prior people management experience

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. 

Salary Range
$238,000—$302,000 USD

Skills

Machine LearningDeep Learning

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