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Embedded Ai Engineer Jobs in Dedham, MA (NOW HIRING)

Vrtx

Principal Full Stack AI Engineer

Boston, MA · On-site

This individual will play a key role in ensuring AI capabilities are embedded into day-to-day work ... Experience in software engineering, AI/application engineering, or platform engineering, including ...

Bevi

Senior Embedded Engineer

Boston, MA · Hybrid

$134K - $176K/yr

Champion the use of AI across the embedded team, applying it to accelerate development, code ... Set the bar for engineering quality through code and design reviews and strong validation practices ...

SimpliSafe

Staff Embedded ML Engineer, Edge AI

Boston, MA

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

SimpliSafe

Staff Embedded ML Engineer, Edge AI

Boston, MA

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

SimpliSafe

Staff Embedded ML Engineer, Edge AI

Boston, MA · On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

Tulip Interfaces

AI Platform Engineer

Somerville, MA · Hybrid

$130K - $180K/yr

Tulip's cloud-native, no-code platform, powered by embedded AI, is driving the digital ... Hands-on experience with LLMs, prompt engineering, agent frameworks, and RAG, built and shipped in ...

Socket.dev

Senior Embedded Engineer

Boston, MA · On-site

$140 - $170/hr

Champion the use of AI across the embedded team, applying it to accelerate development, code ... Set the bar for engineering quality through code and design reviews and strong validation practices ...

Tulip Interfaces

AI Platform Engineer

Somerville, MA · On-site

$130K - $180K/yr

Tulip's cloud-native, no-code platform, powered by embedded AI, is driving the digital ... Hands-on experience with LLMs, prompt engineering, agent frameworks, and RAG, built and shipped in ...

Tulip Interfaces

AI Platform Engineer

Somerville, MA · On-site

$130K - $180K/yr

Tulip's cloud-native, no-code platform, powered by embedded AI, is driving the digital ... Hands-on experience with LLMs, prompt engineering, agent frameworks, and RAG, built and shipped in ...

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Showing results 21-40

All JobsEmbedded Ai Engineer JobsEmbedded Ai Engineer Jobs in Dedham, MA

Embedded Ai Engineer information

See Dedham, MA salary details

$72.5K

$158.8K

$180.2K

How much do embedded ai engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for embedded ai engineer in Dedham, MA is $158,813.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,200.00 and $179,100.00 per year, depending on experience, location, and employer.

What is an embedded AI engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What are the key skills and qualifications needed to thrive as an embedded AI engineer?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an embedded AI engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

What job categories do people searching Embedded Ai Engineer jobs in Dedham, MA look for?

The top searched job categories for Embedded Ai Engineer jobs in Dedham, MA are:

What cities near Dedham, MA are hiring for Embedded Ai Engineer jobs?

Cities near Dedham, MA with the most Embedded Ai Engineer job openings:

Embedded Ai Engineer jobs near you
Infographic showing various Embedded Ai Engineer job openings in Dedham, MA as of July 2026, with employment types broken down into 70% Full Time, 25% Part Time, and 5% Contract. Highlights an 64% Physical, 3% Hybrid, and 33% Remote job distribution, with an average salary of $158,813 per year, or $76.4 per hour.

Software Engineer, Embedded Systems

MatrixSpace

Burlington, MA • Remote

$150K - $185K/yr

Full-time

Re-posted 27 days ago

Job description

Help bring AI and machine learning capabilities to embedded edge platforms by building high-performance software that runs close to the hardware.

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.

We're looking for a hands-on Embedded Software Engineer to build high-performance software that runs close to the hardware. You'll develop production embedded applications in C/C++, optimize software for resource-constrained edge platforms, and work across Linux, networking, and system-level software.

If you're the kind of engineer who can read complex C/C++ code like a book, enjoys understanding entire systems rather than isolated components, and loves solving practical engineering problems, we'd love to talk.

What You'll Do

  • Port, optimize, and enhance platform software for embedded and resource-constrained compute environments.
  • Deploy, validate, profile, and optimize AI/ML-enabled applications on edge hardware.
  • Develop production-quality software using C/C++, Python, Golang, and Linux-based technologies.
  • Collaborate with Data Science teams to integrate AI/ML models into production software pipelines.
  • Work across Linux kernel, device interfaces, networking, and system-level software components.
  • Participate in architecture reviews, code reviews, testing, troubleshooting, and technical planning.

What We're Looking For

This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.

THIS IS NOT A FULLY REMOTE POSITION.

Required

  • Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Robotics, or a related technical field, or equivalent practical experience.
  • 4+ years of professional software engineering experience or equivalent demonstrated expertise
  • Professional experience building, deploying, and maintaining production embedded software systems on edge devices with constrained CPU, GPU, memory, storage, and power resources.
  • Expert-level proficiency in C/C++ with the ability to quickly understand, debug, and extend large existing codebases. This role is not a fit for candidates without deep C/C++ experience. Working knowledge of Golang and Python3.8+ preferred.
  • Strong experience with Yocto-based embedded Linux distributions, including image customization, package management, board support packages, kernel configuration and tuning, and production deployment workflows.
  • Strong debugging, profiling, and performance optimization skills on constrained compute platforms.
  • Ability to collaborate effectively across software, firmware, DevOps, data science, and hardware teams.

Someone Who Will Thrive in This Role

  • Enjoys understanding complete systems—not just individual components.
  • Takes ownership of complex technical problems and follows them through to production.
  • Is comfortable diving into large existing codebases and becoming productive quickly.
  • Values practical, reliable engineering over unnecessary complexity.
  • Collaborates effectively across software, firmware, hardware, and AI teams.
  • Has experience at smaller or fast-growing companies where engineers own broad portions of the product rather than a single isolated component.
  • Has experience developing connected devices, IoT platforms, fleet management systems, robotics, or other distributed edge computing products.

Bonus Points

  • Experience deploying AI/ML models usingTensorRT, ONNX Runtime,PyTorch, TensorFlow Lite, or similar frameworks.
  • Experience with NVIDIA Jetson, CUDA, GPUs, NPUs, or other edge accelerators.
  • Background in radar, RF sensing, robotics, autonomy, perception systems, signal processing, or sensor fusion.
  • Experience with hardware-in-the-loop testing, board bring-up, and embedded platform validation.

At MatrixSpace, software engineering is where advanced sensing technology meets real-world deployment. You'll help bring AI-powered capabilities to edge platforms so our customers can gain actionable insights from complex environments. If that sounds exciting, we'd love to hear from you.