AI Compiler Engineer

Reposted 2 Months Ago
Be an Early Applicant
Hiring Remotely in Norway
Remote
190K-255K Annually
Mid level
Artificial Intelligence • Hardware • Software
The Role
Lead design and implementation of graph compiler optimizations to convert TensorFlow/PyTorch models into IR, improve performance via fusion, quantization, and tiling, collaborate with hardware and ML teams, and mentor engineers to enable efficient deployment on EnCharge inference accelerators.
Summary Generated by Built In

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. 

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. 

Qualifications

  • 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. 

EnCharge AI is an equal employment opportunity employer in the United States.
The salary range for this position is $190,000 to $255,000 USD per year. (Per Year: $195,000 to $265,000 CAD | €110,000 to €160,000 EUR | 1,206,458 to 1,754,848 NOK)
Actual compensation offered will be determined based on job-related knowledge, skills, and experience.

Skills Required

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
  • Ph.D. in relevant field
  • 3+ years in compiler development with focus on AI or ML graph compilers
  • Proficiency with AI graph compiler frameworks (MLIR, Torch-FX)
  • Solid background in hardware architectures (GPUs, TPUs, ASICs) and optimization techniques (fusion, quantization, tiling)
  • Familiarity with neural network operators and code generation
  • Strong understanding of intermediate representations, parsing, and semantic analysis in compiler design
  • Proficiency in C++, Python, or other languages used in compiler development
  • Open-source contributions to AI software frameworks and libraries
  • Demonstrated experience leading and mentoring engineering teams with successful project delivery
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The Company
HQ: Santa Clara, CA
31 Employees
Year Founded: 2022

What We Do

EnCharge AI is a leader in advanced AI hardware and software systems for edge computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

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