Teams at ChipAgents

Build and improve production AI agents for chip design and verification. Responsibilities include evaluating agent performance, diagnosing failures, developing orchestration, memory, context management, and tool interfaces, and converting experiments into scalable, reliable software. The role requires strong backend architecture, production service experience, Python or TypeScript skills, and cross-functional technical leadership.

Build production software that brings machine learning research into EDA workflows and customer environments. Responsibilities include integrating EDA tools and compute infrastructure, developing data pipelines, deploying software in on-premises and restricted networks, creating reusable deployment tooling, and ensuring system reliability and performance. The role collaborates closely with ML researchers, hardware experts, and customer engineering teams while incorporating customer feedback into product development.

Optimize large language model inference across multi-node GPU clusters for production AI agents. Responsibilities include implementing and benchmarking performance improvements, profiling GPU and memory bottlenecks, building evaluation harnesses, integrating model architectures, and applying distributed inference, batching, quantization, and systems-level optimization techniques.