2027 Summer Intern, PhD, Machine Learning Research, Planning/Prediction
About this role
Developing robust deep neural networks to accurately predict future states and plan autonomous vehicle behavior is the core challenge this machine learning researcher will address. The Predictive Planning team builds and deploys advanced machine learning models that process large-scale driving data so that autonomous vehicles navigate complex environments safely.
During the summer, the intern will research, implement, and evaluate generative models for planning and prediction while working alongside industry leaders. This opportunity suits doctoral candidates who want to apply theoretical knowledge to autonomous driving systems and contribute directly to core perception and decision-making infrastructure.
What you will do
- Research, implement, and evaluate state-of-the-art generative models for planning and predictions using JAX.
- Conduct machine learning model experiments to improve autonomous vehicle navigation.
- Produce high-quality and thoroughly tested code for production and research pipelines.
- Collaborate with research, product, and engineering teams to introduce new research concepts.
What you need
- Currently pursuing a PhD degree in Computer Science, Machine Learning, Robotics, or a related field.
- Demonstrated experience with deep learning or reinforcement learning.
- Hands-on experience with modern deep learning libraries such as TensorFlow, JAX, or PyTorch.
- Basic programming skills using Python, C, or C++.
- Strong analytical and debugging skills.
Nice to have
- Publications in top-tier conferences such as ICML, NeurIPS, CVPR, ICCV, ECCV, ICLR, IROS, CoRL, ACL, or EMNLP
- Prior software development or research industry experience, including previous internships
Benefits
- Competitive compensation packages with a housing or relocation bonus
- Medical, dental, and vision insurance
- Fun intern events and networking opportunities
- Free breakfast, lunch, dinner, and snacks
- Free access to Google shuttles
- Onsite gym access
Skills and tech stack
Questions candidates ask
What is the work policy for this internship?
This will be a hybrid onsite internship position based in Mountain View, CA.
What is the compensation for this role?
The expected hourly rate for this full-time position is $85 USD, and interns are eligible to participate in company benefits programs subject to eligibility requirements.
How does the application process work?
Resumes are accepted on a rolling basis until the role is filled. Candidates who wish to be considered for multiple roles must apply to each one individually, up to three roles.