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Senior Embedded Machine Learning Jobs in Massachusetts

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 ...

Draper

Senior Embedded Software Engineer

Cambridge, MA · On-site

$82K - $220K/yr

Additional Expertise in embedded systems, multi-core operating systems, modifying or writing kernel code, machine code, and C & C++. The individual will learn or bring knowledge of multi-core ...

Chewy

Senior Machine Learning Engineer

Boston, MA · On-site +1

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting-edge machine ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting-edge machine ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting-edge machine ...

Draper

Senior Embedded Software Engineer

Cambridge, MA · On-site

$82K - $220K/yr

Additional Expertise in embedded systems, multi-core operating systems, modifying or writing kernel code, machine code, and C & C++. The individual will learn or bring knowledge of multi-core ...

Manulife

Senior Machine Learning Engineer

Boston, MA · Hybrid

$107K - $199K/yr

Senior Machine Learning Engineer Job Duties: Design and implement image processing solutions to enhance operational workflows and fraud detection. Duties include: * Design, develop, and maintain AI ...

Capital One

Sr. Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

VideaHealth

Senior Machine Learning Engineer

Boston, MA · On-site

$170K - $205K/yr

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer ...

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Senior Embedded Machine Learning information

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are some common challenges faced by Senior Embedded Machine Learning Engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What are the key skills and qualifications needed to thrive as a Senior Embedded Machine Learning Engineer, and why are they important?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What does a Senior Embedded Machine Learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.
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:
Senior Embedded Machine Learning jobs near you
Senior Machine Learning Scientist (Sensor Intelligence)

Senior Machine Learning Scientist (Sensor Intelligence)

Whoop

Boston, MA • On-site

$150K - $215K/yr

Other

Posted 14 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.
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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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