AI Research Scientist, Agentic AI and Foundation Models

What you'll do

• Research methods for reasoning, planning, tool use, memory, and reliable execution of multistep tasks.
• Develop pre-training and post-training approaches to strengthen models' technical knowledge and coding abilities.
• Build learning pipelines using curated corpora, synthetic data, agent trajectories, and execution feedback.
• Apply reinforcement learning and adaptation methods to improve agent performance in executable environments.
• Investigate inference-time reasoning and search to improve solution quality and computational efficiency.
• Develop agents for software and hardware workflows including code generation, RTL optimization, and debugging.
• Create benchmarks to measure correctness, generalization, and sustained performance across unfamiliar projects.
• Publish research findings through technical reports, reusable systems, and working demonstrations.

What we're looking for

• Combine research depth with strong engineering skills to turn ambiguous problems into experiments.
• Research methods for reasoning, planning, tool use, memory, and reliable execution of multistep tasks.
• Develop pre-training and post-training approaches to strengthen models’ technical knowledge and coding abilities.
• Build learning pipelines using curated corpora, demonstrations, synthetic data, and agent trajectories.
• Apply reinforcement learning and other adaptation methods to improve agent performance in executable environments.
• Develop agents for software and hardware workflows, including code generation, RTL optimization, and debugging.
• Strong Python and deep learning framework skills with experience running reproducible experiments (preferred).
• Master’s or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related field (preferred).