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Senior Embedded Machine Learning Jobs in Massachusetts

Myomo, Inc

Sr. Embedded Software Engineer

Burlington, MA · On-site

$130K - $140K/yr

Sr. Embedded Software Engineer Department: Engineering Employment Type: Full Time Location ... Foster an environment of continuous learning, improvement, and technical growth. What You'll Bring:

Motional

Senior Embedded Software Engineer

Boston, MA · On-site +1

$134K - $176K/yr

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

RISE Robotics

Sr. Embedded Software Engineer

Somerville, MA · On-site

$135K - $177K/yr

RISE Robotics is leading the way to Zero Emission heavy machinery by providing the world's most ... As a Senior Embedded Software Engineer, you'll play a pivotal role in the development and ...

RISE Robotics

Sr. Embedded Software Engineer

Somerville, MA · On-site

$135K - $177K/yr

RISE Robotics is leading the way to Zero Emission heavy machinery by providing the world's most ... As a Senior Embedded Software Engineer, you'll play a pivotal role in the development and ...

RISE Robotics

Sr. Embedded Software Engineer

Somerville, MA · Hybrid

$135K - $177K/yr

RISE Robotics is leading the way to Zero Emission heavy machinery by providing the world's most ... As a Senior Embedded Software Engineer, you'll play a pivotal role in the development and ...

FORT Robotics

Sr. Embedded Software Engineer I

Boston, MA

$134K - $176K/yr

While autonomous machines offer significant advantages, they also introduce new safety challenges ... As a Senior Embedded Software Engineer, you will own critical subsystems within our embedded stack ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

ASUS Robotics & AI Center Senior Machine Learning Engineer The ASUS Robotics & AI Center is seeking ... Optimize models for real-time performance on embedded and edge computing platforms. * Build and ...

Nanite Inc.

Machine Learning Engineer

Boston, MA

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... The candidate will work with senior leadership and partner projects gaining broad internal and ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... The candidate will work with senior leadership and partner projects gaining broad internal and ...

Cognex

Senior Machine Learning Engineer

Natick, MA

$115K - $225K/yr

The team works across custom hardware, optimized embedded systems, and next-generation algorithm ... Research, design, and implement efficient deep learning models for industrial machine vision tasks ...

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 ...

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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
Sr. Embedded Software Engineer

Sr. Embedded Software Engineer

Myomo, Inc

Burlington, MA • On-site

$130K - $140K/yr

Full-time

Posted 23 hours ago

Job description

Sr. Embedded Software Engineer
Department: Engineering
Employment Type: Full Time
Location: Burlington, MA
Compensation: $130,000 - $140,000 / year
Description
The Senior Embedded Engineer contributes significantly to the development of Myomo's advanced wearable robotics platform, focusing primarily on embedded firmware for microcontrollers and software in the Linux environment. This role combines technical depth, architectural insight, and cross-functional collaboration to deliver safe, secure, and high-quality software in alignment with business and regulatory goals.
The Senior Embedded Engineer collaborates with the cross-functional team and consultants to lead the
design and implementation of the core software for the MyoPro. The role includes helping others on the
team grow with opportunities to establish technical standards, mentor engineers, and contribute to
knowledge sharing.
How You'll Drive Impact:
Software Development
  • Define and maintain software architectures in collaboration with Engineering, IT, and Product Management, prioritizing safety, cybersecurity, reliability, scalability, and maintainability.
  • Design, implement, test and document robust embedded firmware and Linux based software
    solutions.
  • Review code and technical designs with a focus on quality and long-term maintainability.

Cross-Functional Collaboration
  • Translate user needs into robust deliverable solutions in close conjunction with Engineering, Product, Quality, and Clinical.
  • Improve software quality through test-driven development, code standards, and continuous integration practices.
  • Foster an environment of continuous learning, improvement, and technical growth.

What You'll Bring:
  • Bachelor's degree in Computer Science, Engineering or related field.
  • 6+ years' demonstrated expertise in:

o Embedded firmware for electromechanical devices
o Software delivery in regulated environments (e.g. medical, automotive, aerospace)
  • Strong proficiency in at least one embedded-level programming language (e.g., C/C++), and one application-layer language (e.g., Python, Dart, JavaScript/TypeScript)
  • Proficiency with Linux, FreeRTOS and real-time or resource-constrained environments.
  • Experience with communication libraries and interface design for BLE, UART, I2C, SPI, and CAN.
  • Familiarity in Agile methodologies and modern DevOps tools (E.g., Git, CI/CD pipelines, Docker, automated testing frameworks)
  • Strong communication and interpersonal skills; ability to work collaboratively across disciplines.

Preferred:
  • 8+ years' experience in Embedded Engineering.
  • Experience in software development for Class II medical devices.
  • Experience with cybersecurity requirements related to HIPAA, GDPR, and ISO 27001.
  • Experience configuring CI/CD and automated testing frameworks.
  • Ability to debug PCBs using logic analyzers and oscilloscopes.
  • Background in wearable devices, robotics, or human-centered systems.
  • Familiarity with process standards including IEC 62304, ISO 13485, ISO 14971.
  • Familiarity with: STM32 ecosystem, ESP32 ecosystem, or Torizon Linux.

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