Senior Machine Learning Engineer

TETRAMEM INC; San Jose (CA); On-site; USD 110,000 - 300,000; Full time

Job summary

A leading AI technology firm in San Jose seeks a skilled machine learning engineer to develop and optimize lightweight AI models for edge applications. Candidates should have a PhD or over 5 years of experience in relevant fields, with strong skills in ML frameworks like PyTorch and TensorFlow. The role offers a competitive salary range of $110,000 - $300,000 annually, making it an exciting opportunity for innovative engineers to thrive in a collaborative environment.

Qualifications

• 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.
• Expertise in ML frameworks such as PyTorch, TensorFlow, JAX.

Responsibilities

• Develop, optimize, and deploy lightweight machine learning models for edge AI applications.
• Implement and optimize ML models on embedded platforms.
• Collaborate with cross-functional teams to drive innovation.

Skills

Machine learning

Edge AI

C/C++

Python

ML model optimization

Education

PhD or 5+ years in Computer Science, Electrical Engineering, or related fields

Tools

PyTorch

TensorFlow

JAX

Optimum

ONNX

TensorRT

TFLite/LiteRT

ncnn

CoreML

Job description

At TetraMem, we are redefining the future of AI with our groundbreaking innovations in In-Memory Computing. Leveraging world-record multi-level RRAM technology, we deliver highly efficient solutions for AI computations, enabling superior performance and energy efficiency across applications ranging from edge devices to data centers. Our talented team of engineers and industry-leading executives drives this progress, making TetraMem a leader in advanced memory technologies.

If you are passionate about cutting-edge technology and thrive in a fast-paced, collaborative environment, TetraMem is the place for you. Join our global team to shape the future of AI computations and sustainable technology solutions while working at the forefront of innovation. Together, we can make a lasting impact.

Are you ready for new challenges and new opportunities?

Join our team!

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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.

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