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Embedded Machine Learning Jobs in Massachusetts (NOW HIRING)

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 ...

Lancesoft

Embedded Software- Engineer

Lexington, MA · On-site

$120 - $130/hr

G., swarming);demanding real-time embedded software and firmware control;image processing;machine learning;human-machine interaction;space-qualified electronics;and analog and power electronics.

Xforia, Inc.

Principal AI/ML Engineer

Boston, MA · On-site

... on embedded systems. • Working closely with hardware engineers to optimize machine learning models for specific hardware architectures and assisting in system integration. • Conducting ...

MORSE Corp

Data Scientist

Cambridge, MA

You will be part of teams performing Test and Evaluation (T&E) of AI and machine learning models ... embedded systems. * Support the transition of the developed algorithms to software using one or ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in Massachusetts

Embedded Machine Learning information

Will AI replace embedded programmers?

Embedded machine learning involves developing algorithms for resource-constrained devices, and while AI tools can assist with coding and optimization, embedded programmers are essential for designing, implementing, and maintaining these systems. AI is more likely to augment their work rather than fully replace them, especially given the need for specialized knowledge of hardware and real-time constraints.

Is embedded AI a good career?

Embedded machine learning involves developing AI models for hardware with limited resources, such as IoT devices and embedded systems. It is a growing field with demand for skills in hardware programming, C/C++, and AI frameworks, offering opportunities in industries like automotive, healthcare, and consumer electronics.

Is embedded systems still a good career in 2026?

Embedded Machine Learning remains a strong career in 2026 as industries increasingly adopt AI-powered devices and IoT solutions. Professionals with skills in hardware programming, real-time systems, and machine learning frameworks like TensorFlow Lite are in demand for developing intelligent embedded applications. Continuous learning and familiarity with microcontrollers, sensors, and embedded software development are essential for long-term growth in this field.

What engineers make $500,000?

Senior engineers in specialized fields such as embedded machine learning, AI, or data science can reach salaries of $500,000 or more, especially with extensive experience, advanced skills in programming and hardware, and leadership roles. High compensation often involves working in high-demand industries, with additional bonuses or stock options contributing to total earnings.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are the most commonly searched types of Embedded Machine Learning jobs in Massachusetts? The most popular types of Embedded Machine Learning jobs in Massachusetts are:
What are popular job titles related to Embedded Machine Learning jobs in Massachusetts? For Embedded Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Massachusetts look for? The top searched job categories for Embedded Machine Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Embedded Machine Learning jobs? Cities in Massachusetts with the most Embedded Machine Learning job openings:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Massachusetts as of June 2026, with employment types broken down into 54% Full Time, 38% Part Time, 4% Temporary, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer - Semantic Reasoning (Highway)

Zoox

Boston, MA • On-site

$189K - $258K/yr

Full-time

Medical, Life, PTO

Posted 27 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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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