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Embedded Machine Learning Jobs in Massachusetts (NOW HIRING)

Spear AI

Embedded DevOps Engineer

Falmouth, MA · On-site

This person will also serve as an informal interface between the embedded software team and the ... Machine Learning engineers. Successful candidates will work well with both teams and bridge the gap ...

Spear AI

Embedded DevOps Engineer

Falmouth, MA · On-site

This person will also serve as an informal interface between the embedded software team and the ... Machine Learning engineers. Successful candidates will work well with both teams and bridge the gap ...

Lutron Electronics

Principal Data Scientist

Boston, MA · On-site

... and deploy scalable machine learning and AI systems that serve as foundational platforms for ... in IoT, embedded systems, or intelligent devices • Experience contributing to patents ...

MORSE Corp

Data Scientist

Cambridge, MA · On-site

$90K - $210K/yr

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 ...

Motional

Senior Software Engineer, Next Gen Compute

Boston, MA · Hybrid

$133K - $175K/yr

... machine learning, sensors, and hardware compute platforms to evolve Motional's on-board vehicle architecture. If you are a software engineer and love the idea of working on embedded AI hardware and ...

Bostondynamics

Sr. Staff, ML Engineer R&D

Waltham, MA

$173K - $225K/yr

As a Sr. Staff ML Research Engineer on the Machine Learning Safety R&D Team, you will join a small ... You will help integrate your algorithms into embedded systems intended to make our robots safe and ...

Boston Dynamics

Sr. Staff, ML Engineer R&D

Waltham, MA · On-site

$173K - $225K/yr

As a Sr. Staff ML Research Engineer on the Machine Learning Safety R&D Team, you will join a small ... You will help integrate your algorithms into embedded systems intended to make our robots safe and ...

MORSE Corp

Lead Data Scientist (TS/SCI)

Cambridge, MA · On-site

$90K - $210K/yr

You will lead teams and strategy for Algorithm Test and Evaluation (T&E) of AI and machine learning ... time embedded systems. Requirements: * US CITIZENSHIP REQUIRED and an Active Top Secret U.S.

STR

Lead Signal Processing Researcher

Woburn, MA

$173K - $216K/yr

... machine learning algorithms, systems analysis, and real-time embedded processor implementation. The Algorithms, Processing and Experimentation (APEX) Group specializes in development of RF/radar ...

STR

Principal Signal Processing Researcher

Woburn, MA

$206K - $284K/yr

... machine learning algorithms, systems analysis, and real-time embedded processor implementation. The Algorithms, Processing and Experimentation (APEX) Group specializes in development of RF/radar ...

Sarepta Therapeutics

Senior AI/ML Engineer

Cambridge, MA · On-site

$114K - $156K/yr

Design, build, and deploy scalable and robust machine learning models embedded in real workflows, with measurable outcomes. * Solution Evaluation and Implementation: Evaluate internal approaches and ...

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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.
Associate Director, Core Algorithms (Sensor Intelligence Group)

Associate Director, Core Algorithms (Sensor Intelligence Group)

Whoop

Boston, MA

Other

Posted 9 days 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 and live longer through a deeper understanding of their bodies and daily lives.

We are seeking an Associate Director of Engineering, Core Algorithms to define and lead WHOOP's strategy for transforming physiological sensor data into real-time, production-grade intelligence. This role owns the technical vision and execution for core algorithm systems that power member-facing experiences across generations of WHOOP devices.

You will operate at the intersection of machine learning, signal processing, and embedded systems, defining multi-year technical direction, scaling high-performing teams, and shaping how WHOOP delivers differentiated edge intelligence at scale. You will lead teams driving innovation in on-device intelligence, translating complex physiological data into scalable, high-quality insights while navigating tradeoffs across accuracy, latency, and efficiency. Your leadership will directly influence how WHOOP delivers meaningful, member-centric experiences across product generations.

RESPONSIBILITIES:

  • Lead and scale high-performing teams of machine learning and signal processing engineers, including senior ICs and tech leads

  • Define and drive the roadmap for core algorithm systems and on-device intelligence

  • Guide key architectural and technical tradeoffs across accuracy, latency, power, and system constraints

  • Deliver end-to-end sensor-driven features from research through production deployment

  • Drive cross-functional execution across Firmware, WHOOP Labs, and Product; align stakeholders and manage complex dependencies
    Establish best practices for algorithm development, validation, integration, and lifecycle management

  • Balance long-term innovation with near-term product delivery

  • Develop technical leaders and foster a culture of execution excellence

QUALIFICATIONS:

  • Proven experience leading engineering teams in machine learning, signal processing, or embedded systems, including managing senior ICs or tech leads

  • Strong track record of delivering sensor-driven algorithms or systems into production environments

  • Experience working across hardware, firmware, and data science boundaries, with a systems-level mindset

  • Demonstrated ability to define and communicate technical strategy and guide teams through ambiguity

  • Experience driving cross-functional programs, aligning stakeholders, and influencing without direct authority

  • Strong communication skills, with the ability to translate complex technical concepts to diverse audiences

  • Passion for building teams, developing talent, and scaling engineering organizations

PREFERRED QUALIFICATIONS:

  • Experience with physiological sensing (e.g., PPG, IMU, ECG) or wearable technologies

  • Experience optimizing models for edge deployment (e.g., quantization, latency, power constraints)

  • Background in health, fitness, or consumer hardware products

  • Experience balancing long-term innovation vs. near-term product delivery

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Whoop logo

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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