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EnCharge AI

Analog in-memory AI hardware and software

Senior Emulation Engineer

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

  • A BS, MS, or Ph.D. in Electrical Engineering, Computer Science, or a related field, plus 7+ years of SoC design experience.
  • Experience with emulation platforms such as Siemens Veloce, Palladium, or ZeBu, and FPGA-based prototyping systems such as proFPGA, HAPS, or Protium.
  • Experience emulating high-speed I/O interfaces such as PCIe and UCIe and memory technologies such as LPDDR and HBM.
  • A solid understanding of digital design, RTL using Verilog/SystemVerilog, and SoC architecture.
  • Proficiency with hardware debug tools, waveform viewers, and logic analyzers.
  • Scripting skills in Python, Tcl, or Perl for automation and infrastructure development.
  • Familiarity with UVM, simulation, and testbench environments.

Responsibilities

  • Set up and maintain Siemens Veloce emulation and prototyping platforms.
  • Adapt SoC designs for emulation and prototyping.
  • Develop and debug emulation testbenches and system-level environments.
  • Support pre-silicon validation, power and performance analysis, and early software bring-up.
  • Participate in silicon bring-up and validation.
  • Collaborate with design and verification teams to isolate design issues and accelerate debugging.
  • Optimize emulation workload performance and reduce turnaround time.
  • Work with firmware and software teams to enable emulator use for operating-system and driver testing.

Desired Qualifications

  • SystemVerilog and UVM-based verification experience.
  • Hands-on software development experience with C/C++.

About the Company

EnCharge AI

Analog in-memory AI hardware and software

EnCharge AI designs and sells AI-accelerating hardware and software for edge-to-cloud workloads, focusing on analog in-memory computing. Its products include chiplets, ASICs, PCIe cards, and flexible software that integrates across platforms. The approach uses semiconductor design to implement analog in-memory computing for fast AI processing with lower power and smaller footprint, compatible with existing systems. Compared with competitors, it prioritizes sustainability with lower CO2 emissions and total cost of ownership, backed by a leadership team with 20+ years in AI hardware and a track record of 350 million chips shipped, 150 patents, and 300 publications, and aims to democratize advanced AI by making it affordable and environmentally sustainable.

Company size
51-200
Company stage
Series B
Total funding
$162.9M
Headquarters
Santa Clara, CA
Founded
2022

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