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• Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
• Work closely with hardware and software teams to integrate ML models into production systems.
• Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
• Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
• Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
• Provide technical leadership and mentorship to junior engineers.
• Publish research findings, present at conferences, and contribute to open-source projects when applicable.
  

Responsibilities

• Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
• Work closely with hardware and software teams to integrate ML models into production systems.
• Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
• Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
• Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
• Provide technical leadership and mentorship to junior engineers.
• Publish research findings, present at conferences, and contribute to open-source projects when applicable.
  

Requirements

• 5+ years of experience or PhD in Computer Science, Electrical Engineering, or related fields.
• Strong experience in machine learning, with a focus on edge AI and lightweight model deployment.
• Expertise in ML frameworks such as PyTorch, TensorFlow, JAX.
• Proficiency in programming languages such as C/C++, Python, and experience with ML model optimization.
• Ability to work independently and collaboratively in a fast-paced startup environment.
  

Experience in one or more of the following areas considered a strong plus:

• Understanding of ML compiler and runtime design.
• Experience working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
• Familiarity with hardware acceleration techniques.
• Experience in embedded system development.
  

Salary Range: $110,000 - $300,000 / year

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Strategy/Planning and Information Technology

• Industries

  Computer Hardware Manufacturing

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Medical insurance

Vision insurance

401(k)

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