Full-Time

Senior NPU Architect

EnCharge AI

EnCharge AI

51-200 employees

Analog in-memory AI hardware and software

Compensation Overview

$180k - $240k/yr

Remote in USA + 1 more

More locations: Remote in Canada

Remote

Bachelor's, Master's, PhD

Category
Hardware Engineering (1)
Required Skills
Verilog
Python
Machine Learning
C/C++

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Requirements
  • BS or MS in Electrical Engineering, Computer Science, or a related field with 5-8 years of relevant experience. Preferred: Ph.D. in a related field with 2-4 years of relevant experience.
  • Understanding in computer architecture, digital design, and micro-architecture concepts
  • Familiarity with AI/ML algorithms, frameworks, and workloads
  • Programming experience in C/C++ and Python
  • Experience with Hardware Description Languages such as Verilog or SystemVerilog
Responsibilities
  • Define and develop the spec, architecture, and micro-architecture of key architecture modules (such as the in-memory compute unit, on-chip network, and memory orchestration units) based on the requirements of the workloads and software deployment flow
  • Contribute to the modeling of aforementioned key architecture modules in the companys C++ simulation framework to ensure a functional implementation of the features
  • Collaborate with the design verification team to deliver a strategy and infrastructure for the testing of the architecture features within said modules
  • Work with the software team and other architects to analyze the performance and efficiency of the architecture modules for key workloads, identify performance bottlenecks, and guide architectural decisions
  • Stay up to date with the latest trends and research in AI workloads, architectures, and applications to help define a path for the future generations of architectures
Desired Qualifications
  • Ph.D. in a related field with 2-4 years of relevant experience

EnCharge AI develops hardware and software for artificial intelligence computation, ranging from edge devices to cloud servers. The company utilizes analog in-memory computing through chiplets, ASICs, and PCIe cards to process AI tasks directly within memory, which reduces the power and space required for complex calculations. Unlike competitors using traditional digital methods, EnCharge AI offers significantly lower CO2 emissions and a lower total cost of ownership by integrating its specialized technology into the existing semiconductor supply chain. The company's goal is to democratize advanced AI by making it economically viable and sustainable for businesses to solve large-scale human challenges.

Company Size

51-200

Company Stage

Series B

Total Funding

$162.9M

Headquarters

Santa Clara, California

Founded

2022

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Simplify Jobs

Simplify's Take

What believers are saying

  • February 13, 2025 Series B raised over $100 million from Tiger Global and Samsung Ventures.
  • EN100 offers 200+ TOPS in 8.25W, attracting OEMs for on-device AI.
  • CES 2026 highlighted on-device AI demand, directly matching EnCharge's edge-to-cloud pitch.

What critics are saying

  • EnCharge lacks broad commercial shipments; 2025 launch claims still need OEM design wins.
  • NVIDIA, Qualcomm, and Intel dominate client AI silicon, crushing EnCharge's pricing power.
  • If EN100 misses volume production in 2026, EnCharge fails as a hardware startup.

What makes EnCharge AI unique

  • EnCharge's analog in-memory chips perform matrix math inside memory, slashing energy use.
  • EN100 launched May 29, 2025 with M.2 and PCIe forms for laptops, workstations.
  • Princeton roots, Naveen Verma leadership, and 150 patents support technical credibility.

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Benefits

Health Insurance

401(k) Retirement Plan

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-3%

2 year growth

-4%
Electronics For You
Sep 23rd, 2025
Run Advanced AI Locally On Laptops and Workstations

EnCharge AI has introduced the EN100 accelerator to run AI inference directly on local devices.

StartupHub AI
May 31st, 2025
EnCharge AI Raises $144M for Chips

EnCharge AI, an AI chip startup from Princeton University, has raised $144 million to advance its analog in-memory computing technology. Their EN100 AI accelerator chip offers improved performance per watt, enabling advanced AI on laptops and edge devices while reducing energy use. The funding will help expand their technology and software suite. Investors include Tiger Global, Samsung Ventures, and others. The company is poised for growth in the AI PC and edge device market.

Associated Press
Apr 17th, 2025
EnCharge AI Expands Leadership After $100M Series B

EnCharge AI has appointed Jason Huang as VP of Finance and Leslie Szeto as Director of HR following a $100 million Series B funding round. Huang will enhance financial strategy for growth, while Szeto will focus on talent acquisition and organizational development. These hires support EnCharge's transition from development to commercialization of its AI accelerator products. Huang and Szeto bring extensive experience in high-growth transitions, IPOs, and acquisitions.

TechNews
Feb 18th, 2025
EnCharge AI secures $100M for AI chip

EnCharge AI has secured over $100 million in a Series B funding round, bringing its total funding to over $144 million. The company is developing a new AI accelerator chip that aims to match desktop GPU performance with only 1% of the power consumption. Their chip, which uses analog capacitors for computation, is expected to launch later this year for mobile devices, PCs, and workstations, with commercialization planned for 2025.

EE News Europe
Feb 14th, 2025
EnCharge AI raises $100m from Samsung, Foxconn

EnCharge AI raises $100m from Samsung, Foxconn.