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Embedded Machine Learning Internship Jobs in Boston, MA

Motional

Senior Embedded Software Engineer

Boston, MA · On-site

$149K - $198K/yr

Design test harnesses for embedded software components and full systems * Provide technical ... Experience deploying Machine Learning models. * Experience working with GPUs. * Experience working ...

Motional

Senior Embedded Software Engineer

Boston, MA · On-site +1

$149K - $198K/yr

Design test harnesses for embedded software components and full systems * Provide technical ... Experience deploying Machine Learning models. * Experience working with GPUs. * Experience working ...

Whoop

Embedded Engineer

Boston, MA · On-site

$105K - $145K/yr

... learning, and engineering effectiveness. QUALIFICATIONS: * The ability to obtain and maintain a US ... internships, academic projects, research, or industry experience. * Proficiency in C/C++ and ...

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Embedded Machine Learning Internship information

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$27.7K

$46.3K

$95.6K

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

As of Jun 11, 2026, the average yearly pay for embedded machine learning internship in Boston, MA is $46,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,300.00 and $50,000.00 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 the most commonly searched types of Embedded Machine Learning jobs in Boston, MA? The most popular types of Embedded Machine Learning jobs in Boston, MA are:
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Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in Boston, MA as of June 2026, with employment types broken down into 1% Internship, 40% Full Time, 55% Part Time, 2% Temporary, 1% Contract, and 1% Nights. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $46,263 per year, or $22.2 per hour.

Machine Learning Engineer - Semantic Reasoning (Highway)

Zoox

Boston, MA

$189K - $258K/yr

Full-time

Medical, Life, PTO

Posted 13 days ago

Job description

The Scene Understanding Semantic Reasoning team at Zoox builds the high-performance reasoning engines that allow our autonomous vehicles to navigate complex driving environments and high-speed roads. We translate sensor data and detected objects into deep semantic understanding, ensuring our robots make human-level decisions in real-time.

We are seeking experienced engineers passionate about the intersection of robotics and cutting-edge AI. In this role, you will focus on critical initiatives alongside partner Perception and motion planning teams to develop production-grade multi-task transformers, and integrate cutting-edge Vision Language Action (VLA) model outputs to build comprehensive spatial representations for our fleet. You will tackle the inherent unpredictability of urban driving on highways & freeways to improve range and accuracy, ensuring our vehicles remain safe and resilient at all times.

In this role, you will...

  • Model Training & Deployment: Design, train, and deploy deep learning models for semantic reasoning, specifically tailored to achieve the extended spatial range and high fidelity required for high-speed highway environments.

  • Cross-Functional Collaboration: Collaborate with the Scene Intelligence, Semantic Grounding, and PCP Mapping teams to adapt and elevate the unified machine learning stack for highway scenarios.

  • Requirements & Validation: Partner with downstream motion planning teams to define semantic representation requirements, establish robust validation workflows, and ensure model outputs meet strict safety and clearance metrics.

  • Optimization: Optimize deep learning models for real-time inference efficiency, ensuring low-latency execution within the rigorous compute constraints of the Zoox vehicle platform.

  • Edge Case Resolution: Investigate and resolve perception-related regressions and edge cases found in high-speed driving simulations and live fleet data.

  • Strategic Architecture: Contribute to the long-term "North Star" architecture for Perception Semantic Reasoning, paving the way for scalable fleet deployment across new vehicle platforms.

Qualifications

  • MS (3-5 years) or PhD (0-2 years) in Computer Science, Robotics, Electrical Engineering, or a related field, with professional software engineering experience - ideally in autonomous driving, robotics, or computer vision.

  • Deep understanding of 2D/3D computer vision, semantic segmentation, and deep learning architectures.

  • Exceptional programming skills in modern C++ and Python.

  • Hands-on experience with modern deep learning frameworks like JAX or PyTorch.

  • Proven track record of deploying real-time machine learning models on resource-constrained embedded systems or on-bot hardware.

Bonus Qualifications

  • Prior experience dealing with highway autonomous driving scenarios and their specific mapping/perception challenges.

  • Familiarity with state-of-the-art, BEV, Sparse Transformer architectures and Vision-Language Models (VLMs).

  • Strong publication record in top AI conferences or journals (e.g., CVPR, ICCV, ECCV, ICML, NeurIPS).

$189,000 - $258,000 a year
Base Salary Range
 
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
 
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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