2027 Summer Intern, PhD, Machine Learning, Computer Vision

You will

• Analyze and characterize internal feature representations of deep multimodal perception foundation models.
• Validate model performance on large-scale autonomous vehicle sensor datasets and simulation environments.
• Train, fine-tune, and evaluate deep neural networks to improve model performance.
• Inspect perception foundational model to derive signal on data quality.
• Implement or augment data pipeline to improve data quality.

You have

• Currently enrolled in a PhD program in Computer Science, Robotics, Electrical Engineering, or a related technical field.
• Experience programming in Python.
• Practical experience training, fine-tuning, and evaluating deep learning models for computer vision or multimodal perception (e.g., using PyTorch, JAX, or TensorFlow).
• Solid understanding of modern neural architectures (e.g., Vision Transformers, multi modal sensor encoders).

We prefer

• Research experience or publications in multimodal deep learning models, or vision foundational models.
• Hands-on experience working with multi-camera and/or 3D LiDAR perception systems in robotics or autonomous driving.
• Experience evaluating large-scale perception systems under practical settings.

Additional information

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.

Pay and benefits

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