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Embedded Machine Learning Jobs in Boston, MA (NOW HIRING)

Draper

Senior Machine Perception Researcher

Cambridge, MA · On-site

$82K - $220K/yr

Draper's Perception and Embedded Machine Learning Group seeks an engineer to help develop, integrate, and deploy advanced perception systems, including for autonomous vehicles and robots able to ...

Draper

Senior Machine Perception Researcher

Cambridge, MA · On-site +1

$82K - $220K/yr

Draper's Perception and Embedded Machine Learning Group seeks an engineer to help develop, integrate, and deploy advanced perception systems, including for autonomous vehicles and robots able to ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... IoT devices, or embedded systems is highly desirable. * Excellent problem-solving skills ...

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 ...

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 ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in Boston, MA

Embedded Machine Learning information

See Boston, MA salary details

$76K

$166.6K

$189K

How much do embedded machine learning jobs pay per year?

As of Jun 21, 2026, the average yearly pay for embedded machine learning in Boston, MA is $166,636.00, according to ZipRecruiter salary data. Most workers in this role earn between $142,900.00 and $187,900.00 per year, depending on experience, location, and employer.

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 Boston, MA? The most popular types of Embedded Machine Learning jobs in Boston, MA are:
What are popular job titles related to Embedded Machine Learning jobs in Boston, MA? For Embedded Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Boston, MA look for? The top searched job categories for Embedded Machine Learning jobs in Boston, MA are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Boston, MA as of June 2026, with employment types broken down into 70% Full Time, 15% Part Time, 7% Temporary, 4% Contract, and 4% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $166,636 per year, or $80.1 per hour.
Senior Machine Learning Scientist (Sensor Intelligence)

Senior Machine Learning Scientist (Sensor Intelligence)

Whoop

Boston, MA • On-site

$150K - $215K/yr

Full-time

Posted 12 hours ago

Job description

At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.
WHOOP is seeking a Senior Machine Learning Scientist to join the Sensor Intelligence Group (SIG), a cross-functional team collaborating across WHOOP Labs, Firmware, and Machine Learning and Research. This role focuses on developing compact machine learning models for edge deployment and is central to scaling AI systems that power WHOOP's most foundational health features. In this role, you'll develop next-generation, personalized AI from prototyping to productization, ultimately delivering personalized coaching to millions of WHOOP members.
RESPONSIBILITIES:
  • Research, prototype, and productize lightweight deep learning models suitable for resource-constrained edge targets
  • Drive deep learning model customization and compression strategies such as distillation, pruning, fine-tuning, and quantization-aware training
  • Collaborate with product teams to define member experience targets and with cloud-focused machine learning teams to implement distributed AI systems
  • Lead build/buy decisions by evaluating commercial and open-source model performance for WHOOP use cases
  • Stay current in Edge AI industry trends and best practices and mentor junior team members

QUALIFICATIONS:
  • Bachelor's degree in Computer Science, Electrical/Computer Engineering, Applied Mathematics, or a related field; Master's or PhD degree preferred
  • 5+ years of experience as a Machine Learning Scientist or similar role with a focus on advanced development, preferably related to voice and/or text-based conversational systems
  • Demonstrated experience training, fine-tuning, and deploying state-of-the-art deep learning architectures to resource-constrained embedded targets
  • Experience pre-training and fine-tuning small language models and/or building natural language understanding (NLU) models than run on resource-constrained targets
  • Experience with cloud platforms (AWS or GCP) and familiarity with modern MLOps practices such as CI/CD, model versioning, monitoring, and observability
  • Strong communication and collaboration skills across cross-functional teams
  • Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions

ADDITIONAL DESIRABLE EXPERIENCE:
  • Experience deploying deep learning models to microcontrollers or other resource-constrained edge devices using toolchains such as TFLite/LiteRT or ExecuTorch, and with inference libraries such as CMSIS-NN or CMSIS-DSP
  • Experience developing machine learning models for consumer-facing products
  • Experience building multi-modal datasets, including speech, video, text, or physiological signals, for human-AI interaction
  • Familiarity with time-series foundation models and self-supervised learning methods

This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.
At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company's long-term growth and success.
The U.S. base salary range for this full-time position is $150,000 - $215,000 Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.
In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.
These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate's specific qualifications, expertise, and alignment with the role's requirements.
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About Whoop

Sourced by ZipRecruiter

At WHOOP, we're on a mission to unlock human performance. WHOOP empowers users (Olympians, Professional Athletes, Fitness Enthusiasts, etc) to perform at a higher level through a deeper understanding of their bodies and daily lives.

Industry

Fitness and sports centers

Company size

501 - 1,000 Employees

Headquarters location

Boston, MA, US

Year founded

2012

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