Staff Software Engineer, Perception Evaluation
Waymo - Mountain View, CA
Apply NowJob Description
OverviewWaymo is an autonomous driving technology company with the mission to be the world's most trusted driver. 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. Waymo has provided over ten million rider-only trips, driven over 100 million miles on public roads, and conducted tens of billions in simulation across 15+ U.S. states.The Perception Evaluation team at Waymo is at the forefront of autonomous driving, ensuring the safety and reliability of our self-driving technology. We develop and utilize cutting-edge tools and methodologies to rigorously assess the performance of our Perception systems. We are seeking a Staff Software Engineer to play a pivotal role in shaping the future of transportation by directly impacting the quality and reliability of Waymo's autonomous this hybrid role, you will report to a Staff Technical Lead Manager.ResponsibilitiesLead Advanced Evaluation Framework Design: design and develop innovative evaluation frameworks to assess perception system performance, particularly in new and diverse urban environments; define technical specifications and ensure novate with AI in Evaluation Methodologies: develop and implement cutting-edge evaluation methodologies and scalable pipelines; leverage advancements in large-scale AI models to enhance analysis, generate deeper insights, and pioneer new ways to assess performance.Utilize Simulation and Reference Data Systems: drive the use of large-scale inference and simulation systems to establish performance benchmarks, validate perception capabilities, and identify potential perception challenges in various scenarios.Drive End-to-End Platform Delivery: own end-to-end delivery of a robust discovery evaluation platform that supports rapid iteration and meets Waymo’s city-expansion tegrate Evaluation with ML Development Cycles: collaborate with ML and Data Infrastructure teams to ensure evaluation findings feed into the data-driven model development loop, accelerating training and system improvement.Resolve Complex Technical Challenges: proactively identify, troubleshoot, and resolve complex technical hurdles in perception evaluation, delivering actionable feedback under tight deadlines.Qualifications8+ years of experience designing and building complex, scalable systemsDemonstrated technical leadership in defining long-term strategy, roadmaps, and guiding teams from ambiguous requirements to high-impact deliverablesAbility to work effectively across diverse teams and communicate technical concepts clearlyDeep expertise in evaluating ML systems at scale, including metrics design, experimentation, large-scale data analysis, and statisticsHands-on experience with ML infrastructure and modern AI concepts (including foundation models or similar) and their practical applicationProficiency in C++ and Python in production environmentsExcellent problem-solving skills, clear technical communication, and strong end-to-end ownershipPreferred qualificationsFamiliarity with autonomous vehicle systems, particularly Perception, including data pipelines and evaluation processesExperience with data analysis, visualization, and triage tools; ability to identify improvement areasExperience designing efficient data processing workflows for large datasetsFamiliarity with or experience in Generative AI or AI agentsCompensation and BenefitsSalary Range: $238,000—$302,000 USDThe expected base salary range for this full-time position across US locations is listed above. Actual starting pay will be based on job-related factors, including location, experience, training, education, and skill level. Your recruiter can share more about the specific range for the role location or remote work.Waymo employees are eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous company benefits program, subject to eligibility requirements. #J-18808-Ljbffr
Created: 2025-09-21