ZipRecruiter

Log In

1

Embedded Machine Learning Internship Jobs in Berkeley, CA

Bland

Machine Learning Intern

San Francisco, CA · On-site

Machine Learning Research Intern, Audio As a Research Intern at Bland, you will own a focused ... We scope internships around a single meaningful question that can be answered in the time you have.

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... custom embedded GPU targets. • Deep understanding of profiling tools and debugging resource ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... custom embedded GPU targets. • Deep understanding of profiling tools and debugging resource ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

What we're looking for * 4+ years of non-internship professional MLE experience. * Deep expertise ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Atoms

Staff Machine Learning Engineer

San Francisco, CA · On-site

What we're looking for * 10+ years of non-internship professional MLE experience. * Deep expertise ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Atoms

Staff Machine Learning Engineer

San Francisco, CA · On-site

What we're looking for * 10+ years of non-internship professional MLE experience. * Deep expertise ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

What we're looking for * 4+ years of non-internship professional MLE experience. * Deep expertise ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

next page

Showing results 1-20

All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Internship JobsEmbedded Machine Learning Internship Jobs in Berkeley, CA

Embedded Machine Learning Internship information

See Berkeley, CA salary details

$31.2K

$52.1K

$107.8K

How much do embedded machine learning internship jobs pay per year?

As of Sep 7, 2026, the average yearly pay for embedded machine learning internship in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 per year, depending on experience, location, and employer.

What is an embedded machine learning internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an embedded machine learning internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What are the key skills and qualifications needed to thrive as an embedded machine learning intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.

What are popular job titles related to Embedded Machine Learning Internship jobs in Berkeley, CA?

For Embedded Machine Learning Internship jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Internship jobs in Berkeley, CA look for?

The top searched job categories for Embedded Machine Learning Internship jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Embedded Machine Learning Internship jobs?

Cities near Berkeley, CA with the most Embedded Machine Learning Internship job openings:

Embedded Machine Learning Internship jobs near you

Machine Learning Engineer

NR Consulting

Fremont, CA • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
NR Consulting is a company focused on innovative technology solutions, and they are seeking a Machine Learning Engineer to develop and deploy lightweight machine learning models for edge AI applications. The role involves collaborating with hardware and software teams, optimizing models for embedded platforms, and providing technical leadership to junior engineers.
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.
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:
NR Consulting is an information technology consulting firm that offers contingent hiring, direct hires, and managed IT services. Founded in 2017, the company is headquartered in Boulder, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

Apply