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 builds the brains of Waymo'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:
Team: Systems Intelligence and Machine Learning (SIML)
Subteam: ML Frameworks and Efficiency
Description:
Scale the world’s most trusted driver by delivering state-of-the-art ML capabilities, efficient and reliable infrastructure, and an ecosystem built for rapid innovation at Waymo.
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:
- Understand the problem the current LPM model is trying to solve along with its details
- Improve/extend the current RL infrastructure to support LPM model training needs
- Profiling and understanding slowness, maintain and improve the training efficiency
- Identify promising new RL technologies and integrate to our infrastructure
You have:
- Currently pursuing a PhD/Master degree in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a related technical field
- Fundamental understanding of machine learning, deep learning and reinforcement learning
- Familiar with modern frameworks (JAX, Flax, PyTorch, or TensorFlow)
- Strong software development skills with Python
We prefer:
- Has experience on ML or RL with hands-on projects
- Has experience on large scale ML system infrastructure
- Has experience in working with autonomous driving or relevant technologies
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. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.
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
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 PhD Pay
$85—$85 USD