Phinity Labs, Inc.

United States
7 Total Employees
Year Founded: 2025

Jobs at Phinity Labs, Inc.

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17 Days AgoSaved
In-Office
San Francisco, CA, USA
Artificial Intelligence • Machine Learning • Semiconductor • Automation
Phinity is seeking exceptional applicants to join its AI research lab, which develops autonomous AI agents for chip design and tape-out. The work spans reinforcement learning environments, agent infrastructure, evaluation systems, computer architecture, silicon design, and formal verification. This open application is intended for candidates interested in redefining how advanced chips are built through AI-driven engineering automation.
17 Days AgoSaved
In-Office
San Francisco, CA, USA
Artificial Intelligence • Machine Learning • Semiconductor • Automation
Lead semiconductor physical design from synthesis through tapeout, defining block-to-full-chip flows, PDN and clock-tree strategies, PVT corners, custom-cell and memory characterization, and PPA optimizations. Collaborate with physical design engineers to optimize utilization, power grids, and clock networks while delivering tapeout-ready designs using autonomous prompt-to-GDS capabilities.
17 Days AgoSaved
In-Office
San Francisco, CA, USA
Artificial Intelligence • Machine Learning • Semiconductor • Automation
Leads business strategy, partnerships, company-wide operations, organizational planning, commercial relationships, contracting, negotiations, and scalable internal processes. Works closely with founders to align priorities, advance initiatives, support growth, and coordinate teams across an AI research lab focused on autonomous chip design.
17 Days AgoSaved
In-Office
San Francisco, CA, USA
Artificial Intelligence • Machine Learning • Semiconductor • Automation
Develops data, environments, and evaluation systems for AI agents performing hardware engineering tasks. Responsibilities include scaling experimental environments, profiling and benchmarking unreleased models, and conducting research at the intersection of hardware engineering and reinforcement learning. The role requires low-level systems or VLSI experience, strong research judgment, rigorous engineering, ownership, and leadership.