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

Waymo LLC; Mountain View (CA); On-site; USD 96,000 - 117,000; Full time

Benefits offered by this job

Housing/relocation bonus

Medical, dental, and vision insurance

Free meals onsite

Free shuttle access

Job summary

Waymo LLC in Mountain View is offering a hybrid onsite internship with a focus on model optimization for perception and foundation models used in autonomous driving. You will work on optimizing and deploying ML models, collaborating with cross-functional teams across hardware and software domains.

The role emphasizes Python and DL frameworks (JAX, Flax, PyTorch, or TensorFlow) and includes hands-on tasks in quantization, latency reduction, and multi-task learning for real-time on-vehicle

Qualifications

• Pursuing a PhD or Master’s in CS, EE, ML, Robotics, or related field.
• Strong software and DL development skills in Python and ML frameworks.
• Solid understanding of foundation models and multi-task learning.
• Experience with model compression, LoRA/QLoRA, or quantization techniques.

Responsibilities

• Design, implement, and benchmark LoRA/QLoRA modules in JAX/Flax for Vision Transformer backbones.
• Develop dual-level distillation pipelines 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.
• Conduct extensive empirical ablations and evaluate perception metrics on large-scale autonomous driving datasets across geographic domains.

Skills

Python

JAX/Flax

PyTorch/TensorFlow

Transformer architectures

Multi-task learning

Education

PhD or Master’s in CS/EE/ML/Robotics

Tools

JAX

Flax

TensorFlow

PyTorch

Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

Software Engineering buildsthe brains ofWaymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.

The subteam for this role will be:

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!

You will:

• 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

You have:

• 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

We prefer:

• 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)

General Perks

• Help solve challenging problems with a direct impact on the company
• Competitive compensation packages with a housing/relocation bonus (if applicable)
• Medical, dental, and vision insurance
• Fun intern events and networking opportunities

Onsite Perks

• Free breakfast, lunch, dinner, and snacks
• Free access to Google shuttles
• Onsite gym

Note: This will be a hybrid onsite internship position.

The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.

Hourly Masters Pay

$70—$70 USD

Hourly PhD Pay

$85—$85 USD