Staff Tech Lead Manager (Perception, Sensor Pipelines)

• 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 Director and manage and grow a team of engineers working on Perception ML pipelines
• Manage large teams of software engineers working on vertical pipelines that solve a portfolio of Perception product challenges using ML. Work on 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

Benefits

• Medical, dental, and vision insurance for employees and dependents
• Employee assistance programs focused on mental health
• Personalized workplace adjustments for diverse needs and abilities, including physical, mental, and neurodivergent considerations
• Access to mental health apps
• Onsite wellness centers
• Counseling services
• Second medical opinion for you and your loved ones
• Support programs including menopause benefit
• Medical advocacy program for transgender employees
• Competitive compensation
• Regular bonus and equity performance grant opportunities
• Generous 401(k) and regional retirement plans
• Annual cross-company compensation review and pay equity analysis
• 1-on-1 financial coaching
• Fertility and growing family assistance
• Parental leave and baby bonding leave
• Backup childcare
• Survivor income benefit
• Elder care and support
• Caregiver leave
• Paid time off, including vacation, bereavement, sick leave, parental leave, disability, and holidays
• Jury duty leave
• Military leave
• Hybrid work model with remote work opportunities also available
• Educational reimbursement
• Peer learning and coaching platform
• Donation matching programs
• Volunteer hours
• Employee resource groups
• Internal community groups and local culture clubs
• Inspiring spaces to work, recharge, and collaborate with fellow Waymonauts
• On-site meals and snacks
• Fitness centers, massage programs, and ergonomic support
• On-demand fitness, wellbeing, and cooking classes
• Commuter benefits

• 8+ years of industry experience
• 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
• 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