Senior Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer with a long-term contract, located remotely in San Jose, CA. Requires 8+ years of experience or a PhD, expertise in ML frameworks, and proficiency in C/C++ and Python, focusing on edge AI applications.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 30, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Atlanta, GA
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🧠 - Skills detailed
#PyTorch #Python #ML (Machine Learning) #AI (Artificial Intelligence) #TensorFlow #Leadership #Programming #Model Optimization #Deployment #C++ #Model Deployment #Computer Science
Role description
Role: Senior Machine Learning Engineer
Location: San Jose, CA (Remote)
Duration: Long Term
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:
8+ 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 working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
Familiarity with hardware acceleration techniques.
Experience in embedded system development.
Role: Senior Machine Learning Engineer
Location: San Jose, CA (Remote)
Duration: Long Term
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:
8+ 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 working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
Familiarity with hardware acceleration techniques.
Experience in embedded system development.
