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Hourly Embedded Machine Learning Jobs in Boston, MA

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 ...

CVS Health

Senior Machine Learning Engineer

Wellesley, MA

$111K - $222K/yr

We're looking for a Senior Machine Learning Engineer to help build and scale the next generation of ... hourly rate or base annual full-time salary for all positions in the job grade within which this ...

Socket.dev

Senior Embedded Software Engineer

Boston, MA · On-site

$140 - $160/hr

Deploy, optimize, and support multiple computer vision and machine learning models running concurrently on embedded devices. * Analyze system performance including compute utilization, memory ...

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 JobsHourly Embedded Machine Learning JobsHourly Embedded Machine Learning Jobs in Boston, MA

Hourly Embedded Machine Learning information

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$76K

$166.6K

$189K

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

As of Aug 16, 2026, the average yearly pay for hourly 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.

What is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

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 Hourly Embedded Machine Learning jobs in Boston, MA?

For Hourly Embedded Machine Learning jobs in Boston, MA, the most frequently searched job titles are:

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The top searched job categories for Hourly Embedded Machine Learning jobs in Boston, MA are:

What cities near Boston, MA are hiring for Hourly Embedded Machine Learning jobs?

Cities near Boston, MA with the most Hourly Embedded Machine Learning job openings:

Hourly Embedded Machine Learning jobs near you

Senior Machine Learning Scientist (Sensor Intelligence)

Whoop

Boston, MA • On-site

$150K - $215K/yr

Full-time

Re-posted 26 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 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.
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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