Senior Software Engineer (Training Efficiency)

• The Waymo ML Infrastructure team works with Research and Production teams to develop models in Perception and Planning that are core to our autonomous driving software
• We help our partners by offering the best solutions for the entire model development lifecycle
• These solutions are developed in close collaboration with teams at Google
• They are geared towards both scaling models and solving problems unique to ML for autonomous driving
• You will improve the runtime efficiency of input data pipelines for large-scale training workloads
• This is a unique opportunity to work on ML systems and improve on our model training processes
• Design, and improve distributed input data pipelines for large-scale ML training workloads
• Collaborate with researchers and ML engineers to resolve bottlenecks in data pipeline performance
• Improve runtime goodput of ML training workload, including optimizing input data processing systems, ensuring scalability and reliability across distributed environments
• Implement and maintain advanced ML infrastructure tools, including ML Pathways, Grain, JAX, and TensorFlow
• Evaluate and integrate modern technologies to enhance the performance and scalability of ML systems
• Promote best practices for distributed systems architecture and contribute to technical leadership within the team

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

• Proficient in distributed systems design with an understanding of ML data pipeline optimization
• Solid programming skills in Python and C++
• Experience with ML frameworks, including TensorFlow and JAX
• Practical familiarity with profiling tools to uncover performance bottlenecks
• B.S. in Computer Science, Math, or 8+ years equivalent real-world experience
• Hands-on experience libraries like Grain or tf.data service
• MS in Computer Science, Math
• Familiarity with distributed dataflow frameworks like ML Pathways