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Tesla AI Research Engineer VLM Autonomy Robotics United States, California, Palo Alto 920260899
11.04.2025
What You’ll Do What You’ll Bring
- Compute and verify scaling laws for real-world understanding using large GPU clusters and extensive datasets
- Develop and debug large distributed training jobs spanning tens of thousands of GPUs
- Align our pre-trained foundation vision models with large language models for unified perception and language comprehension
- Buildild new human-labeled and synthetic datasets addressing real-world tasks and physical reasoning
- Explore reward functions and SOTA RL techniques to enhance real-world understanding and problem-solving
- Leverage Tesla’s data to create robust evaluation sets focused on real-world scenarios and physical accuracy
- Perform knowledge distillation from larger models to smaller, edge-optimized models deployable across Tesla cars and robots
- Apply quantization, inference-time optimizations, and device-specific tweaks to reduce power consumption and latency
- Deep Learning Background: Experience with large-scale vision-language models, multimodal transformers, or related architectures
- Distributed Systems Expertise: Proven ability to train and optimize models on high-performance clusters (thousands of GPUs)
- Practical Dataset Management: Comfort curating or generating large, diverse datasets—human-labeled, synthetic, or both
- Reinforcement Learning Knowledge: Familiarity with RL algorithms and reward function design, especially for complex real-world tasks
- Hands-On Approach: Willingness to iterate quickly on experimental ideas—from pre-training to final deployment
- Collaboration & Communication: Strong cross-functional skills, able to work with AI research engineers, robotics teams, and software groups
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