Technical Program Manager (Onboard Systems, ML Modeling)

• Waymo’s Technical Program Managers and Program Managers are accountable for Waymo’s roadmap execution by providing thoughtful cross-functional planning, clarity, and proactive risk management
• In the face of complex technical and operational challenges with no established playbooks to follow, we act with thoughtful urgency, driving conversations, discussions, and outcomes
• Our team partners closely with every function of Waymo to structure, own and drive work towards real-world deployments of the Waymo Driver across platforms and geographies
• Drive cross-functional execution and delivery of projects within the onboard team, collaborating with engineering teams, product teams and release management
• Manage project schedules, identify risks and dependencies, and develop mitigation strategies
• Facilitate communication and collaboration between engineering, research, and product teams, ensuring alignment on program goals, milestones, and technical requirements
• Track and report on project/program progress, risks, and key performance indicators (KPIs) to leadership and stakeholders
• Contribute to the strategic planning, objective setting, and technical roadmap for the Waymo Foundation Model program
• Proactively identify and resolve roadblocks and dependencies, coordinating across organizational boundaries

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
• Medical advocacy program for transgender employees
• Counseling services
• Second medical opinion for you and your loved ones
• Support programs including menopause benefit
• 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
• Survivor income benefit
• Elder care and support
• Backup childcare
• 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- Experience with machine learning models, training pipelines, or evaluation frameworks
• Strong analytical, problem-solving, and technical judgment skills
• A Bachelor’s degree in Computer Science, Engineering, or a related technical field
• Excellent communication, interpersonal, and presentation skills, effectively conveying technical concepts to both technical and non-technical audiences
• 5+ years of experience as a Technical Program Manager in a software engineering environment
• A proven track record of successfully managing complex technical projects involving machine learning and/or AI
• Experience with large language models (LLMs), vision language models, generative AI, diffusion models, large-scale model training, data labeling, data generation and packaging for model training
• Strong background in 3D computer vision, sensor fusion (camera, lidar), spatial reasoning, and 3D reconstruction methods (NeRF, Gaussian Splatting)
• Experience with cloud-based machine learning platforms and infrastructure
• Experience with simulation environments for autonomous systems, model validation strategies, and methods to ensure model reliability
• Experience with model evaluation techniques, metrics, time-series analysis, and predictive modeling using sensor data, model optimization, and scaling techniques
• Master’s degree or PhD in a related field