Waymo

Builds self-driving AI and runs a robotaxi service

Senior Staff Systems Engineer - Perception-Planner Risk

Robotics & Autonomous SystemsConfirmed live in the last 24 hours

Full-timeMountain View, CA, USAIn-person

About the Job

Requirements

A bachelor's degree or higher in computer science, mathematics, physics, engineering, or a related field is required.
At least 10 years of engineering experience delivering high-stakes technical roadmaps that resolve architectural friction and deploy business-critical systems is required.
Experience using artificial intelligence productivity tools for analysis and workflow development is required.
Proficiency and experience in vehicular robotics development or evaluation, software development with Python or C++, statistical or predictive modeling, and experimental design and development of metrics for quantitative methods are required.
Deep technical knowledge of at least two of the following is required: state-of-the-art machine learning techniques powering modern perception systems and large end-to-end models; quantitative risk estimation using simulators, preferably with sensors in the loop; or systems engineering fundamentals such as requirements definition and formal verification and validation methods.
A track record of leading complex projects in safety-critical applications with leadership-facing accountability across software, operations, data science, product, and testing is required.
Strong verbal and written communication skills and the ability to manage by influence are required.

Responsibilities

Define the approach for quantitative safety risk analysis across sensing and perception systems engineering, building on Waymo-wide risk assessment and management methodologies.
Design, develop, and implement quantitative methods and statistical models to evaluate end-to-end performance for current and counterfactual sensor suites.
Apply the defined approach to selected events that occur rarely or have scarce operational data, assessing behavioral safety risk across situations such as pedestrian crowds, floods, and degraded sensing in construction zones.
Develop and prototype workflows to determine required performance levels of sensing and perception tasks; support trade studies informing perception hardware or software architectural decisions; estimate exposure to events relevant to perception-driven behavioral risk; and improve the rigor, standardization, execution efficiency, and reporting of end-to-end risk from verification and validation test outcomes in complex contexts.
Expand existing methodologies to support new operational design domains and address emergent challenges.
Collaborate with Onboard Software and Evaluation to map perception evaluation and planner evaluation to end-to-end risk in large models.
Collaborate with Test Engineering to cross-calibrate risk from verification and validation results across methodologies and coverage competencies, and provide actionable data to improve testing tools across public-road and closed-course tests and simulations on logged and synthetic scenarios.
Collaborate with Systems Safety to allocate quantitative risk appropriately across functional insufficiencies.
Communicate complex quantitative findings and recommendations to stakeholders, including senior leadership, to enable safety at scale.
Collaborate within Systems Engineering and cross-functionally with Product, Simulation, and Data Science teams to advance safety and delivery.

Desired Qualifications

A master's degree with thesis or a PhD in machine learning, statistics, robotics, or a related quantitative field is preferred.
Autonomous driving industry experience is preferred.
Experience testing on large-scale infrastructure and deploying production-level safety-critical systems is preferred.
A track record of developing model-driven metrics that influence software or hardware design decisions at scale is preferred.

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.

Waymo's Systems Engineering team works together to blend software and hardware systems in groundbreaking new ways. We set the high performance standards that ensure our vehicles run smoothly and keep passengers safe, then design and perform the tests that validate that performance. We're looking for talented teammates who’ll help us maintain strong teamwork and are passionate about driving results.

You will:

Define the approach for quantitative safety risk analysis across sensing and perception systems engineering, building on top of Waymo-wide risk assessment and management methodologies. You will design, develop, and implement sophisticated quantitative methods and statistical models for evaluating end-to-end performance for current and counterfactual sensor suites.
Apply the defined approach for selected events that occur rarely or have scarce operational data. The generalized goal is to assess behavioral safety risk across a wide variety of situations like interacting with pedestrian crowds, navigating around floods, and degraded sensing in construction zones.
Develop and prototype novel workflows to:

Analyze to determine the required performance levels of various sensing and perception tasks
Support trade studies to inform architectural decisions for perception hardware or software
Estimate exposure of events relevant to perception-driven behavioral risk
Improve quantitative rigor, standardization, efficiency of execution, and reporting of end-to-end risk from V&V test outcomes in complex contexts.

Expand existing methodologies that are crucial for breaking into new operational design domains and addressing emergent challenges
Collaborate closely with:

Onboard Software and Evaluation for mapping perception evaluation and planner evaluation to end-to-end risk in large models
Test Engineering for cross-calibrating risk from V&V results across various methodologies and coverage competencies, and providing actionable data to improve Waymo’s test tooling across public roads/closed course tests and simulations on logged/synthetic scenarios
Systems Safety for appropriate allocation of quantitative risk across functional insufficiencies

Clearly communicate complex quantitative findings and recommendations to diverse stakeholders, including senior leadership, to enable safety at scale. You will collaborate deeply within SysEng and cross-functionally with Product, Simulation, and Data science teams to advance safely and deliver excellence.

You have:

Bachelors or higher degree in computer science, math, physics, engineering, or a related field
10+ years of engineering experience with demonstrated delivery of high-stakes technical roadmaps that successfully resolved architectural friction and deployed business-critical systems
Experience using AI productivity tools for analysis and workflow development
Proficiency and experience in:

Vehicular robotics (development or evaluation)
Software development (Python or C++)
Statistical or predictive modeling
Experimental design and developing metrics for quantitative methods

Deep technical knowledge of at least two of:

State of the art ML techniques that power modern perception systems and large end-to-end models
Quantitative risk estimation using simulators, preferably with sensors-in-loop
Systems engineering fundamentals such as requirements definition, formal verification and validation methods

Track record of leading complex projects in safety critical applications with leadership-facing accountability across software, operations, data science, product, and testing
Excellent verbal and written communication skills, and ability to manage by influence

We prefer:

Masters (with thesis) or PhD in machine learning, statistics, robotics, or a related quantitative field
Autonomy driving industry experience
Experience testing on large-scale infrastructure and deploying production-level safety critical systems
Track record of developing model-driven metrics that influence software or hardware design decisions at scale

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

$272,000—$336,000 USD

Salary Range 272000 - 336000 USD

About the Company

Waymo

Builds self-driving AI and runs a robotaxi service

Waymo builds self-driving technology and uses it to run a ride-hailing service in which passengers summon electric cars with no one behind the wheel. In 2020, it became the first company to open fully driverless rides to the public, starting in metro Phoenix. Its system, the Waymo Driver, pairs cameras, radar and laser sensors called lidar with onboard computers whose AI predicts what nearby people and vehicles will do and drives the car. Riders pay per trip through the Waymo app, or through Uber in some cities, while Waymo and fleet partners keep the cars charged and maintained. Waymo began as a Google project in 2009 and became a separate Alphabet company in 2016; it is based in Mountain View, California.

Company size: 1,001-5,000
Company stage: Debt Financing
Total funding: $32.1B
Headquarters: Mountain View, CA
Founded: 2009

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