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Normal Computing is an applied AI company building foundational hardware and software for the semiconductor industry and critical AI infrastructure. The company operates across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
As an Analog Hardware Engineer, you will design the core mixed-signal technology powering Normal's unconventional computing architecture. You will create unique analog circuits, including library cells and macros, to support a distinctive computational architecture. Working alongside silicon architecture, digital, and layout teams, you will own the end-to-end analog development from clean-sheet circuit design through parasitic extraction and silicon bring-up to unlock unprecedented throughput-per-watt performance.
Key responsibilities include:
- Leading the full analog development cycle including research and exploratory design
- Developing or acquiring analog IP for use in Normal Silicon
- Acquiring or helping direct analog EDA tool development
- Evaluating memory designs, including SRAM, DRAM, and CIM (Computing-in-Memory) architectures
This is a hands-on technical role where you will drive analog design methodology and own critical components of the chip development process from specification through silicon validation.
REQUIREMENTS:
- Demonstrated experience developing analog IP from specification to GDSII in modern technologies, with successful tape-outs and silicon bring-up
- Hands-on experience with memory technologies (SRAM, DRAM) at the core level, including bitcell arrays and peripheral circuits
- Proven ability to design and characterize custom bitcells in both schematic and layout
- Fluency in Cadence design flow: Virtuoso, Spectre, Assembler, Extraction, Layout, HSMC, and Characterization tools
- Deep understanding of noise, variation, and their impacts on silicon performance and reliability
BONUS QUALIFICATIONS:
- Experience leading, taping out, and bringing up CIM (Computing-in-Memory) chips
- Comfort and experience in chip measurement environments for debug and characterization
- Proficiency with AI and/or scripting languages (Python, Perl) to automate design flows and data post-processing
