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Embedded Machine Learning Internship Jobs (NOW HIRING)

Machine Learning Engineer

San Diego, CA · On-site

$122.80K - $184.20K/yr

As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques ... of experience in embedded system development and optimization with application to a specific ...

Machine Learning Researcher

San Jose, CA · On-site

$150K - $290K/yr

Machine Learning Researcher Location: 2550 N First Street Suite 250, San Jose, California 95131 ... Implement POCs in Python/C++ to validate ML ideas on embedded hardware * Conduct research in ...

OR · On-site

Overview We are looking for interns to join Instacart's Economics team. The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in ...

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Embedded Machine Learning Internship information

See salary details

$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.
More about Embedded Machine Learning Internship jobs
What cities are hiring for Embedded Machine Learning Internship jobs? Cities with the most Embedded Machine Learning Internship job openings:
What are the most commonly searched types of Embedded Machine Learning jobs? The most popular types of Embedded Machine Learning jobs are:
What states have the most Embedded Machine Learning Internship jobs? States with the most job openings for Embedded Machine Learning Internship jobs include:
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.
Last Minute AI-Machine Learning Summer Internship (Gen AI - Multimodal)

Last Minute AI-Machine Learning Summer Internship (Gen AI - Multimodal)

Eluvio

Berkeley, CA • On-site

Temporary, Internship

Posted 25 days ago


Job description

If you are an outstanding upper undergrad, recent grad or grad student and are looking for an amazing last-minute Summer Internship - this is the opportunity for you! Eluvio AI is growing fast and we have a new internship position available in our Berkeley HQ!

Eluvio is a highly focused and ambitious team of systems, networking, application, and video software engineers, AI scientists, ML engineers, and security experts working together to implement the vision of the Content Fabric - a decentralized platform for video and commerce with the ambition of serving the world's Internet video. The Eluvio Content Fabric provides an innovative distributed and decentralized video processing framework with just-in-time and personalized experiences, made possible through our state-of-the-art real-time content routing and just-in-time code execution. We are headquartered in Berkeley, CA.

Eluvio uses a wide range of machine learning and deep learning techniques within its content fabric. This position offers an internship opportunity for students with excellent academic records pursuing graduate degrees in computer science, data science, or related fields (or advanced undergraduates) to work in our office with our software engineering team on ML, DL and data science solutions.

Responsibilities

  • Work with the Eluvio AI Machine Learning and Data Science Team
  • Build production level machine learning models on large-scale datasets to increase the intelligence of video/audio content
  • Provide data-driven recommendations and actionable insights on problems such as content understanding/augmentation/location
  • Develop multi-functional learning pipelines
  • Collaborate with product and engineering teams to implement models at scale
  • Help train and develop multimodal learning models using advanced learning techniques including RAG, self-supervised learning, semi-supervised, and transductive learning.

Requirements

Desired Qualifications

  • MSc or PhD student in Computer Science & Engineering/Statistics/Math/Physics, or Advanced Undergraduate
  • Deep classroom experience in data science or machine learning or prior internship
  • Comfortable with Python or R
  • Knowledge of machine/deep learning algorithms (e.g. gradient boosting, CNNs, sequence models) and frameworks/libraries (e.g., Tensorflow, PyTorch, Sci kit-learn)
  • Knowledge of computer vision and natural language processing
  • Strong working experience with large multi-modal and language models preferred
  • Great communication skills, organized, able to multitask and be a team player
  • Ability to balance attention to detail with agile execution

Benefits

Paid summer internship with one of the top Video AI tech companies in the world!

Catered Lunches (really good food)

Great atmosphere, nice colleagues

Summer Party!