Software Engineer 2027 Summer Intern (MS/PhD, Sys Intel & Machine Learning)

• The Model Optimization & ML Runtime team (within Smart Perception / Machine Learning) is responsible for maximizing the capability, efficiency, and hardware performance of Waymo’s cutting-edge perception and foundation models. We bridge the gap between large-scale multi-task ML research (Vision Transformer backbones, 30+ perception heads, multi-sensor fusion) and real-time onboard vehicle deployment across custom automotive accelerators, developing core optimization frameworks (parameter-efficient fine-tuning, quantization, compilation, and quantization-aware training) that power the autonomous Waymo Driver
• Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!
• Design, implement, and benchmark parameter-efficient fine-tuning (LoRA / QLoRA) modules in JAX/Flax for multi-task Vision Transformer backbones
• Develop dual-level distillation pipelines (intermediate feature matching and task-head logit distillation) to mitigate multi-task regressions during large-scale data scaling
• Collaborate with model optimization, quantization, and latency teams to validate static weight folding and low-precision quantization, ensuring zero latency overhead on onboard compute platforms
• Conduct extensive empirical ablations and evaluate perception metrics on large-scale autonomous driving datasets across diverse geographic domains

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
• Support programs including menopause benefit
• Second medical opinion for you and your loved ones
• Counseling services
• Competitive compensation
• Regular bonus and equity performance grant opportunities
• Generous 401(k) and regional retirement plans
• 1-on-1 financial coaching
• Annual cross-company compensation review and pay equity analysis
• Fertility and growing family assistance
• Parental leave and baby bonding leave
• Elder care and support
• Backup childcare
• Survivor income benefit
• 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- Solid theoretical understanding and hands-on experience with deep learning foundation models, Transformer architectures, and multi-task learning
• Experience with model compression, parameter-efficient fine-tuning (e.g., LoRA, QLoRA, adapters), or quantization and knowledge distillation techniques
• Strong software engineering and deep learning development skills in Python and modern frameworks (JAX, Flax, PyTorch, or TensorFlow)
• Currently pursuing a PhD or Master’s in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a related technical field
• Experience training and scaling large vision backbones or multi-modal models on distributed accelerator clusters (TPUs / GPUs)
• Hands-on experience with model quantization (PTQ, QAT, INT8/INT4/MX4), low-precision numerics, or hardware-aware model optimization
• Publication record at top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR)
• Familiarity with autonomous driving perception tasks (3D object detection, semantics, tracking, or pedestrian intent prediction)