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Edge Ai Machine Learning Jobs in Massachusetts (NOW HIRING)

STR

Machine Learning Engineer

Woburn, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Nucs AI

Machine Learning Scientist

Berlin, MA · On-site +1

About Nucs AI Nucs AI is revolutionizing cancer care through cutting-edge AI and medical imaging ... The Opportunity Nucs AI is looking for a Machine Learning Scientist to deepen our ML research ...

STR

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

STR

Machine Learning Engineer

Boston, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

STR

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

TripleTen

$152K/yr

We're looking for the person who brings an AI and Machine Learning curriculum to life for students: hosts the live sessions, reviews the work, runs the model and system review boards, and sets the ...

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Edge Ai Machine Learning information

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

How to become an edge AI machine learning engineer?

To become an edge AI machine learning engineer, develop strong skills in machine learning, embedded systems, and programming languages like Python and C++. Gain experience with hardware platforms such as NVIDIA Jetson or Raspberry Pi, and learn to optimize models for low-power, resource-constrained environments. Earning certifications in AI, embedded systems, or IoT can also enhance your qualifications.
What are the most commonly searched types of Edge Ai Machine Learning jobs in Massachusetts? The most popular types of Edge Ai Machine Learning jobs in Massachusetts are:
What are popular job titles related to Edge Ai Machine Learning jobs in Massachusetts? For Edge Ai Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Edge Ai Machine Learning jobs in Massachusetts look for? The top searched job categories for Edge Ai Machine Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Edge Ai Machine Learning jobs? Cities in Massachusetts with the most Edge Ai Machine Learning job openings:
Edge Ai Machine Learning jobs near you
Infographic showing various Edge Ai Machine Learning job openings in Massachusetts as of July 2026, with employment types broken down into 28% Internship, and 72% Full Time. Highlights an 100% In-person job distribution.

Senior Machine Learning Engineer Ai/Machine Learning/Boston

Motion Recruitment Partners, LLC

Boston, MA • On-site

$133K - $175K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Job description


A full-service product development consultancy specializing in medical devices, robotic systems, and automation is hiring a Senior Machine Learning Engineer. In this position, you'll be responsible for owning the entire ML lifecycle, transforming raw sensor data into reliable models that run on constrained hardware. You will collaborate closely with embedded, hardware, and software teams to design and implement data pipelines, as well as optimize and deploy models for signal processing and anomaly detection on real-world devices.
As a core team member, you'll also help build out MLOps infrastructure, participate in sensor selection and integration, and ensure seamless validation and delivery of AI features within device software. You'll document model development to support both internal quality processes and regulatory submissions, ensuring your solutions are robust, maintainable, and production ready.
Required Skills & Experience
  • Strong proficiency in Python
  • Hands on experience in PyTorch or TensorFlow
  • Experience deploying models to edge using TFLite, ONNX, CoreML, TensorRT, or equivalent
  • Experience building sensor data pipelines
  • Proficiency with MLOps
  • Solid Software engineering fundamentals
  • Proficiency in C or C++
Desired Skills & Experience
  • 5 years of machine learning engineering or applied ML
  • Experience with physiological signal processing for medical or wearable applications
  • Background in robotics, or autonomous systems
  • Experience in a startup or small team
  • Degree in a relevant field
What You Will Be Doing
Daily Responsibilities
  • 100% Hands On
  • Develop and troubleshoot workflows for collecting, cleaning, and organizing sensor data.
  • Build and refine ML models for real-time device applications and performance improvements
  • Work closely with firmware teams to embed and test AI features on hardware platforms
  • Set up and oversee tools for tracking experiments, automating evaluations and managing deployments
  • Analyze model behavior, ensure reliability and resolve issues to maintain high-quality outputs
The Offer
  • Bonus OR Commission eligible
You will receive the following benefits
  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Paid Time Off (PTO)
  • 401(k) {including match - if applicable}
Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

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