2026 Summer Intern – AI/ML Intern – Sensor Encoder (PhD)
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About this role
About the Team:
The Sensor Encoder team is dedicated to advancing the state-of-the-art in AI for autonomous vehicles, with a specific focus on encoders for camera, lidar and radar. We are a collaborative, forward-thinking group of researchers and engineers tackling some of the most complex challenges in autonomy and machine learning related to sensor data processing.
About the Role:
As an intern on the sensor encoder team, you’ll work on cutting-edge projects advancing vehicle autonomy, developing algorithms and models that shape the future of self-driving technology. This internship provides experience with real-world AI/ML systems, collaboration with leading researchers and engineers, and mentorship from experienced AV researchers to grow your skills in the autonomous vehicle industry.
What You’ll Do:
- Lead research and prototyping of advanced machine learning methods, such as foundation models, vision-language architectures, self-supervised learning.
- Prototype ML models that improve perception, prediction, or decision-making for autonomous driving.
- Collaborate with cross-functional teams, including research, robotics, and systems engineering.
- Participate in technical discussions, share insights, and work towards publishing results.
Required Qualifications:
- Currently pursuing or in the process of obtaining a Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field.
- Solid understanding of modern machine learning techniques, especially deep learning architectures (e.g., transformers, generative models, multimodal learning).
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
- Research experience in AI/ML, demonstrated through coursework, academic projects, or publications.
- Strong problem-solving skills and a collaborative mindset.
- Strong communication and presentation skills.
- Experience working and communicating cross functionally in a team environment.
- Able to work fulltime, 40 hours per week
Preferred Qualifications:
- Familiarity with autonomous vehicles or advanced driver assistance systems (ADAS).
- Experience working with large-scale datasets and training ML models in high-performance computing environments.
- Intent to return to degree program after the completion of the internship/co-op
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, CVPR, ICML, ICLR, AAAI, ECCV, RSS, ICRA, CoRL, or similar.
- Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches
- Graduating between December 2026 and June 2027.