Job Description:
Join Intel’s cutting-edge NPU (Neural Processing Unit) project, as part of a multidisciplinary team that spans compiler development, model enablement, and large language model (LLM) engineering. You will play a key role in building the software stack that powers next-generation AI workloads on Intel’s NPUs, enabling efficient, dynamic, and scalable deployment of advanced machine learning models—including quantized and dynamic models.
Responsibilities
 

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• Design, implement, and optimize compiler features for Intel NPU architectures, ensuring high performance and efficient code generation.
  
• Enable and optimize machine learning models—including LLMs—for deployment on Intel NPUs, focusing on quantization, dynamic execution, and hardware-specific acceleration.
  
• Collaborate with other teams to productionize new models and support emerging AI workloads.
  
• Develop and maintain model conversion, quantization, and deployment pipelines, ensuring correctness, reproducibility, and compliance with Intel’s standards.
  
• Benchmark, profile, and debug models and software components to identify and resolve performance bottlenecks.
  
• Stay current with the latest advancements in compilers, model optimization, quantization, and LLM research, and integrate best practices into the NPU software stack.
  
• Write clear technical documentation and provide support to internal and external users.
   
  

Qualifications
 

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• Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, or related field.
  
• Proven expertise in C/C++ with strong software design and optimization skills.
  
• Solid understanding of AI model optimization techniques such as quantization, pruning, and distillation.
  
• Familiarity with large language models and their deployment requirements.
  
• Knowledge of computer architecture, hardware acceleration, and low-level performance tuning.
  
• Proficiency with Linux environments, virtualization, and CI/CD workflows.
  
• Strong analytical, problem-solving, and cross-team collaboration skills in fast-moving technical settings.
  
• Experience with modern compiler infrastructures (e.g., LLVM, MLIR) or code generation for custom accelerators is a plus.
  
• Hands-on experience with AI frameworks (OpenVINO, TensorFlow, PyTorch, ONNX), Python, and performance tools for NPUs, GPUs, or FPGAs is a plus.
  
• Experience developing dynamic execution or runtime systems that handle variable input sizes and adaptive behavior is a plus.
  
• Familiarity with collaborative tools (GitHub, Jira) and open-source contribution practices is a plus.
  

Benefits

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  Performance bonus
  
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  Medical subscription
  
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  Dental subscription
  
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  Extra days off
  
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  Flexible work schedule
  
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  Meal vouchers
  
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  Holiday vouchers