2027 Summer Intern, MS/PhD, Software Engineer, ML Frameworks and Efficiency
About The Position
Waymo is an autonomous driving technology company focused on building the Waymo Driver and improving access to mobility while reducing traffic crashes. The Software Engineering organization develops the software that enables the Waymo Driver to perceive its surroundings, make decisions, and safely transport people. This position is on the Systems Intelligence and Machine Learning (SIML) team, within the ML Frameworks and Efficiency subteam, which aims to deliver advanced machine-learning capabilities, efficient and reliable infrastructure, and an ecosystem for rapid innovation. This is a 2027 summer internship for a candidate pursuing a master's or PhD degree. Interns partner with industry leaders on impactful projects and have opportunities to apply their knowledge and expand their skills. The role focuses on understanding the current LPM model and its problem, extending reinforcement-learning infrastructure to support LPM training, improving training efficiency, and evaluating and integrating new reinforcement-learning technologies. The position is hybrid and onsite.
Requirements
- Currently pursuing a master's or PhD degree in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a related technical field.
- Fundamental understanding of machine learning, deep learning, and reinforcement learning.
- Familiarity with modern frameworks such as JAX, Flax, PyTorch, or TensorFlow.
- Strong software development skills with Python.
Nice To Haves
- Hands-on project experience in machine learning or reinforcement learning.
- Experience with large-scale machine-learning system infrastructure.
- Experience working with autonomous driving or related technologies.
Responsibilities
- Understand the problem the current LPM model is designed to solve and its details.
- Improve or extend current reinforcement-learning infrastructure to support LPM model training needs.
- Profile and investigate slowness, and maintain and improve training efficiency.
- Identify promising new reinforcement-learning technologies and integrate them into the infrastructure.
Benefits
- Competitive compensation packages, with a housing or relocation bonus if applicable.
- Medical, dental, and vision insurance.
- Intern events and networking opportunities.
- Free breakfast, lunch, dinner, and snacks onsite.
- Free access to Google shuttles.
- Onsite gym.
- Company benefits programs, subject to eligibility requirements.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
