PhD ML Research Intern — Autonomous Driving

Talanto; Mountain View, Northern (CA, KY); Hybrid; USD 99,000 - 135,000; Full time

Benefits offered by this job

Hybrid onsite internship

Benefits eligibility

Job summary

Talanto seeks a PhD internship in autonomous driving research in Mountain View, CA. This hybrid onsite role offers hands‑on work on perception and multimodal models, with a focus on data, learning and evaluation.

You will analyze internal feature representations, design active learning and data curation workflows, and train and evaluate deep neural networks for vision or multimodal perception using PyTorch, Python, and C++. Experience with Vision Transformers is a plus.

Qualifications

• Currently enrolled in a PhD program in Computer Science, Robotics, Electrical Engineering, or a related quantitative field.
• Experience programming in Python and C++.
• Practical experience training, fine‑tune, 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).

Responsibilities

• Analyze and characterize internal feature representations of deep multimodal perception foundation models.
• Design and implement active learning and intelligent data curation algorithms to identify rare, safety‑critical edge cases.
• Explore automated data labeling and validation workflows leveraging modern Vision‑Language Models (VLMs).
• Train, fine‑tune, and evaluate deep neural networks to improve model performance.
• Validate model performance on large‑scale autonomous vehicle sensor datasets and simulation environments.

Skills

Python

C++

Deep Learning

Vision Transformers

Multimodal perception

Education

PhD candidate in CS/Robotics/EE

Tools

PyTorch

JAX

TensorFlow

Job description

Talanto seeks a PhD internship in autonomous driving research in Mountain View, CA. This hybrid onsite role offers hands‑on work on perception and multimodal models, with a focus on data, learning and evaluation.

You will analyze internal feature representations, design active learning and data curation workflows, and train and evaluate deep neural networks for vision or multimodal perception using PyTorch, Python, and C++. Experience with Vision Transformers is a plus.