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

Waymo is an autonomous driving technology company building the Waymo Driver to improve access to mobility and save lives lost to traffic crashes. The Software Engineer intern will develop and optimize machine learning models and runtime systems for autonomous driving perception, collaborating on fine-tuning, distillation, quantization, and evaluation across large-scale datasets.

What you'll do:

• 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

What they're looking for:

• Currently pursuing a PhD or Master's in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a related technical field
• Strong software engineering and deep learning development skills in Python and modern frameworks (JAX, Flax, PyTorch, or TensorFlow)
• 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
• Publication record at top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR)
• Hands-on experience with model quantization (PTQ, QAT, INT8/INT4/MX4), low-precision numerics, or hardware-aware model optimization
• Experience training and scaling large vision backbones or multi-modal models on distributed accelerator clusters (TPUs / GPUs)
• Familiarity with autonomous driving perception tasks (3D object detection, semantics, tracking, or pedestrian intent prediction)

Benefits:

• Competitive compensation packages with a housing/relocation bonus (if applicable)
• Medical, dental, and vision insurance
• Fun intern events and networking opportunities
• Free breakfast, lunch, dinner, and snacks
• Free access to Google shuttles
• Onsite gym
• Hybrid onsite internship position