Role at a glance
- Job function
-
AI & Data AI Research & Applied Science
- Salary
- $85/hr
- Location
- Mountain View, California, United States San Francisco, California, United States
- Work arrangement
- Hybrid
- Employment
- Internship
- Experience
- Familiarity with methods of sampling from large models Experience with post-training methods such as SFT, RL, and preferences Modern deep learning frameworks such as PyTorch and Jax We prefer: Experience working with open and closed loop decision making models in robotics Experience with synthetic data generation and evaluation Prior projects using LLM-as-a-judge
- Education
- Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering or a related technical field
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Role Summary
The PhD research intern will develop and evaluate methods for using synthetic driving data in model training. The role combines synthetic and logged data and includes communicating methods for synthetic data generation and training.
What You'll Do
- Build tools for sampling, selecting, and discarding synthetic driving data, guided by testable hypotheses about how the data will...
- Train and evaluate models using mixtures of synthetic and logged data.
- Present and write about methods for synthetic data generation and training.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering, or a related technical field; familiarity with methods of sampling from large models; experience with post-training methods such as SFT, RL, and preferences; and modern deep learning frameworks such as PyTorch and Jax.
Required
- Familiarity with methods of sampling from large models
- Experience with post-training methods such as SFT, RL, and preferences
- Modern deep learning frameworks such as PyTorch and Jax
Preferred
- Experience working with open and closed loop decision making models in robotics
- Experience with synthetic data generation and evaluation
- Prior projects using LLM-as-a-judge
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.
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:
- Build tools for sampling, selecting, and discarding synthetic driving data with testable hypotheses of how that data will lead to improvement
- Train and evaluate models with mixtures of synthetic and logged data
- Present and write about methods for synthetic data generation and training
You have:
- Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering or a related technical field
- Familiarity with methods of sampling from large models
- Experience with post-training methods such as SFT, RL, and preferences
- Modern deep learning frameworks such as PyTorch and Jax
We prefer:
- Experience working with open and closed loop decision making models in robotics
- Experience with synthetic data generation and evaluation
- Prior projects using LLM-as-a-judge
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.
About the company
Waymo
Large Enterprise
Waymo is a leading autonomous driving technology company, originally a part of Google's parent company Alphabet Inc. Established in 2009, Waymo focuses on developing self-driving cars and innovative transportation solutions designed to enhance mobility and safety on the roads. By employing advanced artificial intelligence and machine learning algorithms, the company aims to revolutionize personal and shared transportation, making it more accessible and efficient. Waymo's efforts contribute significantly to the future of autonomous vehicles and the ongoing shift towards smart transportation systems.