12 days ago
Santa Clara, CA, USASenior / Staff+
Base Salary
$244k - $413k/yr
Responsibilities
- Design and implement large-scale multi-modal architectures for autonomous driving.
- Develop pretraining and fine-tuning strategies using extensive fleet data.
- Research and integrate cross-modal alignment to enhance model performance.
- Collaborate with infrastructure engineers to scale training across thousands of GPUs.
- Conduct systematic evaluation and visualization of model behavior.
- Contribute to model deployment optimization, including quantization and latency–accuracy trade-offs.
Requirements
- Master’s degree or higher in Computer Science, Electrical/Computer Engineering, or related field with 5-8+ years of experience in deep learning.
- Strong proficiency in PyTorch and modern transformer-based model design.
- Experience in large-scale pretraining or multi-modal modeling.
- Deep understanding of representation learning and self-supervised or reinforcement learning techniques.
- Familiarity with distributed training and large-batch optimization.
Benefits
- Collaborative, research-driven environment with access to massive real-world data and industry-scale compute.
- Opportunity to work with top-tier researchers and engineers.
- Direct impact on the next generation of intelligent mobility systems.
- Competitive compensation package.
- Snacks, lunches, dinners, and fun activities.
Tech Stack
PyTorch
Categories
AI & MLData Science