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# Mid-Level Machine Learning Engineer

- **Company:** TETRAMEM INC
- **Location:** San Jose, CA, United States
- **Experience:** Experienced
- **Salary:** $110,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Audio Signal Processing, C++ (Programming Language), Field-Programmable Gate Array (FPGA), Python (Programming Language), Machine Learning, Tensorflow, Systems Architecture, Application Specific Integrated Circuits, Pytorch, Information Technology, Low Latency, ONNX (Open Neural Network Exchange) Format, Hardware Acceleration, TensorRT
- **Published:** May 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f8d063287ce5f53a

## About the Role

* 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.

## Description

* 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.


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