Full-Time

AI Compiler Engineer

EnCharge AI

EnCharge AI

51-200 employees

Analog in-memory AI hardware and software

No salary listed

India

In Person

Residency in India required; no remote option stated.

Bachelor's, Master's, PhD

Category
Software Engineering
Required Skills
Python
TensorFlow
PyTorch
C/C++

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Requirements
  • Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred)
  • 3+ years in compiler development, with a strong focus on AI or ML graph compilers
  • Proficiency in AI graph compiler frameworks (e.g., MLIR, Torch-FX)
  • Solid background in hardware architectures (e.g., GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling
  • Familiarity with neural networks operators and code generation
  • Strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design
  • Proficiency in C++, Python, or other programming languages commonly used in compiler development
  • Open-source contributions to AI software frameworks and libraries is a plus
  • Demonstrated experience leading and mentoring engineering teams with successful project delivery
Responsibilities
  • Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization
  • Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges
  • Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations
  • Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR)
  • Implement parsing, semantic analysis, and IR generation for deep learning frameworks
  • Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers
  • Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations

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.