Principal Engineer, AI Hardware Research Engineer (7870)

TSMC•San Jose, CA

5d•$130,000 - $180,000•Hybrid

About The Position

We are seeking an exceptional AI Hardware Research Engineer to join our team in San Jose. In this role, you will drive innovation at the intersection of technology, architecture, and algorithms to tackle the most critical challenges in AI hardware design. This is an opportunity to shape the future of AI computing through high-impact research and cross-disciplinary collaboration. You will join us in our San Jose office, operating on a hybrid work schedule with 4 days in-office.

Requirements

Ph.D. in Electrical Engineering or Computer Science, or a related STEM field.
Recent Ph.D. graduate (0–2 years of industry experience) with a distinguished academic record and a focus on semiconductor-related research.
Hands-on experience or deep technical background in most of the following areas: Modeling and simulation of AI hardware and systems, Hardware and disaggregated system architectures for LLM inference, Accelerator, memory, and networking architectures, Advanced memory and packaging technologies, including photonics and thermal management, Large language model (LLM) algorithms and frameworks.

Nice To Haves

Innovative thinker: passionate about exploring novel ideas and pushing boundaries
Self-driven and proactive: able to identify high-impact problems and take initiative
Excellent communicator: skilled at conveying complex ideas clearly in both written and verbal form
Quick learner: adept at rapidly acquiring expertise in new domains
Independent problem solver: capable of delivering results with minimal supervision
Collaborative team player: thrives in a multidisciplinary research environment

Responsibilities

Conduct workload-level performance evaluation and technology benchmarking for AI systems by developing modeling and simulation capabilities
Provide strategic guidance to the broader R&D Organization on technology development directions, based on system-level evaluations and projections of future industry trends
Identify opportunities to fully leverage TSMC packaging and memory technologies within novel AI hardware architectures
Develop innovative technology and architecture concepts to address scaling and efficiency bottlenecks in next-generation AI hardware