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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-timeIndiaNo salary listed

About the Job

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

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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