Mid-Level Machine Learning Engineer

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