Description

Develop, optimize, and deploy lightweight machine learning models for edge AI applications, with a focus on audio processing.

This role is on-site.

Responsibilities

• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
• Improve inference efficiency using quantization, pruning, and knowledge distillation.
• Collaborate 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.
• Provide technical leadership and mentorship to junior engineers.

Required Skills

• 5+ years of experience or PhD in Computer Science, Electrical Engineering, or related fields.
• Strong experience in machine learning, specifically edge AI and lightweight model deployment.
• Expertise in ML frameworks: PyTorch, TensorFlow, or JAX.
• Proficiency in C/C++ and Python.
• Experience with ML model optimization and compression techniques.
• Ability to work independently and collaboratively in a startup environment.

Preferred Skills

• Understanding of ML compiler and runtime design.
• Experience with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.

Key Skills

Education

Any Gradute