You will:- Design and conduct experiments on large-scale generative or foundation model training recipes
- Analyze model evaluation metrics to identify performance bottlenecks and optimization strategies
- Collaborate with researchers and engineers to integrate novel techniques into production training pipelines
You have:- Currently enrolled in a PhD program in Computer Science, AI, Robotics, or a related quantitative field
- Solid background in deep learning, transformer architectures, and generative modeling
- Proficiency in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow)
We prefer:- Publications at top-tier AI/ML conferences (NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV)
- Experience with distributed training across multi-node GPU/TPU clusters
- Familiarity with autonomous driving perception, prediction, or planning problems
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.
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
