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Embedded Machine Learning Internship Jobs (NOW HIRING)

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Machine Learning Engineer Internship

Austin, TX · On-site

During this internship, you will be embedded in our Perception team. The Perception team serves as ... Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning ...

Georgia IT Inc

machine Learning

Peachtree City, GA

Machine Learning in Peachtree City, GA, USA Target Rate - Open Rates WWS ID - 111803 (And 111800 ... Experience in embedded software development (TI OMAP/Jacinto, NXP imx6, Renesas, NVidia, Qualcomm ...

Compunnel

Machine Learning Engineer

Freeport, ME · Remote

Machine Learning Engineer Location: Freeport Maine Remote Must haves: * 4+ years ML experience ... and in embedded systems * Collaborate with data scientists to identify and analyze data ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

... of experience in embedded system development and optimization with application to a specific ... machine learning (e.g., Python, R, C, C++). • 1+ year of experience using statistics and ...

Motorola

Machine Learning Engineer

Los Angeles, CA

Stay current with the latest Machine Learning research for wireless and embedded systems. * Perform ... other related duties of which the above are representative. REQUIRED QUALIFICATIONS * Bachelor of ...

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Embedded Machine Learning Internship information

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$25.5K

$42.6K

$88K

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

As of Jun 3, 2026, the average yearly pay for embedded machine learning internship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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 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 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.
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Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Mid-Level Machine Learning Engineer

Mid-Level Machine Learning Engineer

TetraMem - Accelerate The World

San Jose, CA

$110K - $200K/yr

Other

Posted 16 days ago

Job description

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:

  • 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.


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 - $200,000 / year

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