10 months ago
Palo Alto, CA, USAMid Level
Responsibilities
- Post-train frontier models to perform semiconductor design and verification tasks.
- Develop reinforcement learning environments for LLMs and multimodal agents.
- Create reward functions, scaling strategies, evaluation frameworks, datasets, benchmarks, and feedback pipelines.
- Collaborate with hardware design, verification, and computer architecture experts to define evaluation metrics, constraints, and simulation conditions.
- Run large-scale RL fine-tuning and post-training experiments.
- Apply reinforcement learning or curriculum learning to structured reasoning and symbolic domains.
Requirements
- Experience creating and scaling reinforcement learning environments for LLMs or multimodal agents.
- Experience building evaluation datasets and benchmarks for complex reasoning or design tasks.
- Experience working with hardware and verification experts to define metrics, constraints, and simulation conditions.
- Experience designing reward functions and feedback pipelines balancing correctness, performance, and design efficiency.
- Experience running large-scale RL fine-tuning or post-training experiments for frontier models.
- Experience applying reinforcement learning or curriculum learning to structured reasoning or symbolic domains.
Categories
AI ResearchML Engineering
