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Machine Learning Hardware Jobs in Sunnyvale, CA (NOW HIRING)

Conduit

Machine Learning Engineer

San Francisco, CA · On-site

You are technical enough to own the full pipeline: data collection on real factory hardware, manual ... Experience with industrial machine vision (Cognex, Keyence, Zebra / Adaptive Vision, MVTec Halcon)

Apple Inc.

Machine Learning FEA Engineer

San Francisco, CA · On-site

$150.40 - $277.60/hr

San Francisco Bay Area, California, United States Hardware Imagine what you can do here! We are ... The machine learning models will drive rapid design iterations by assessing potential risks and ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

... hardware innovation at the speed of software. We are building an AI-driven simulation software ... Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ...

Human Archive

Machine Learning Engineer

San Francisco, CA · On-site

$120 - $160/hr

To achieve this, we build custom hardware products, deploy them globally at scale, and publish ... The Opportunity As a Machine Learning Engineer, you'll work on multimodal perception, VLA training ...

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All JobsMachine Learning Hardware JobsMachine Learning Hardware Jobs in Sunnyvale, CA

Machine Learning Hardware information

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How much do machine learning hardware jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for machine learning hardware in Sunnyvale, CA is $28.86, according to ZipRecruiter salary data. Most workers in this role earn between $20.58 and $32.74 per hour, depending on experience, location, and employer.

What is a machine learning hardware?

A Machine Learning Hardware job involves designing, optimizing, and developing specialized hardware to accelerate machine learning workloads. Professionals in this field work on hardware architectures like GPUs, TPUs, FPGAs, and custom accelerators to improve efficiency, performance, and power consumption. They collaborate with software engineers and data scientists to optimize hardware-software co-design. This role requires expertise in computer architecture, parallel computing, and low-level programming.

What are the typical day-to-day responsibilities for a machine learning hardware engineer?

As a Machine Learning Hardware engineer, your daily tasks often include collaborating with data scientists and software engineers to understand computational requirements, designing and prototyping hardware accelerators, and optimizing existing architectures for improved performance and efficiency. You might work with simulation tools to model new designs, validate hardware functionality, and troubleshoot issues during integration. The role typically involves both independent technical work and teamwork across hardware and AI/ML departments. This position requires keeping up to date with emerging technologies to ensure your solutions remain cutting-edge and competitive in the fast-evolving landscape of artificial intelligence.

What are the key skills and qualifications needed to thrive in the machine learning hardware position, and why are they important?

To thrive in Machine Learning Hardware, you need a solid background in computer engineering, digital design, and machine learning principles, often supported by a degree in electrical engineering, computer engineering, or a related field. Familiarity with hardware description languages (such as VHDL or Verilog), simulation tools, FPGA/ASIC development platforms, and possibly certifications in hardware design or ML accelerators is valuable. Collaboration, problem-solving, and the ability to communicate complex technical ideas effectively are essential soft skills. These skills enable you to design and optimize specialized hardware solutions that accelerate machine learning workloads and foster interdepartmental innovation.

What are the most commonly searched types of Machine Learning Hardware jobs in Sunnyvale, CA?

The most popular types of Machine Learning Hardware jobs in Sunnyvale, CA are:

What are popular job titles related to Machine Learning Hardware jobs in Sunnyvale, CA?

For Machine Learning Hardware jobs in Sunnyvale, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Hardware jobs in Sunnyvale, CA look for?

The top searched job categories for Machine Learning Hardware jobs in Sunnyvale, CA are:

Machine Learning Hardware jobs near you
Infographic showing various Machine Learning Hardware job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $60,037 per year, or $28.9 per hour.

Mid-Level Machine Learning Engineer

TetraMem - Accelerate The World

San Jose, CA • On-site

Full-time

Re-posted 18 days ago

Job description

Job Summary:
TetraMem is a company focused on accelerating the world through innovative technology, and they are seeking a Mid-Level Machine Learning Engineer to develop and optimize machine learning models for edge AI applications. The role involves collaborating with hardware and software teams, providing mentorship, and researching state-of-the-art ML techniques to enhance model efficiency.
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.
Qualifications:
Required:
• 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.
• Ability to provide mentorship, technical guidance, and career development support to junior engineers and interns.
Preferred:
• 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.
Company:
TetraMem is developing cutting-edge analog computing solutions for AI applications, offering exceptional performance with ultra-low power consumption. Founded in 2018, the company is headquartered in Newark, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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