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EnCharge AI

Analog in-memory AI hardware and software

AI Compiler Engineer

Systems Software EngineeringConfirmed live in the last 24 hours
Full-time$190k - $255k /yrRemote

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field is required.
  • At least 3 years of compiler development experience with a strong focus on artificial intelligence or machine learning graph compilers is required.
  • Proficiency in artificial intelligence graph compiler frameworks such as MLIR and Torch-FX is required.
  • A solid background in hardware architectures such as graphics processing units, tensor processing units, and application-specific integrated circuits is required.
  • Experience with optimization techniques such as fusion, quantization, and tiling is required.
  • Familiarity with neural network operators and code generation is required.
  • A strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design is required.
  • Proficiency in C++, Python, or other programming languages commonly used in compiler development is required.

Responsibilities

  • Architect, design, and implement optimizations for artificial intelligence model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
  • Work closely with machine learning researchers, hardware engineers, and software developers to design and deploy artificial intelligence models while understanding and addressing hardware-specific challenges.
  • Develop performance optimizations for neural network models, including layer fusion, operator fusion, and graph-level transformations.
  • Develop compiler optimizations and passes that convert high-level artificial intelligence models from frameworks such as TensorFlow and PyTorch into intermediate representations.
  • Implement parsing, semantic analysis, and intermediate-representation generation for deep learning frameworks.
  • Research and integrate advancements in compiler design, machine learning model optimizations, and hardware acceleration into graph compilers.
  • Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations.

Desired Qualifications

  • A Ph.D. in Computer Science or Electrical Engineering is preferred.
  • Open-source contributions to artificial intelligence software frameworks and libraries are a plus.
  • Demonstrated experience leading and mentoring engineering teams with successful project delivery is desirable.

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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