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Remote Embedded Ai Jobs in Boston, MA (NOW HIRING)

OLIVER Agency - North America

Design Director

Boston, MA · On-site +1

Remote (PST) or San Francisco Bay Area About the role: We're pairing craft with AI velocity--and we need a Design Director to lead it. We've launched an embedded, AI-native creative studio for one of ...

3B Staffing LLC

AI Solutions Engineer

Boston, MA · Remote

$60 - $77.50/hr

Remote Duration: 6 months Agentic AI leader responsible for building multi-agent systems while ... User Interface Layer (Chat UI, API Gateway, Slack/Teams, Voice, Embedded BI tools) * Orchestration ...

3B Staffing LLC

AI Solutions Engineer

Boston, MA · Remote

$60 - $77.50/hr

Remote Duration: 6 months Agentic AI leader responsible for building multi-agent systems while ... User Interface Layer (Chat UI, API Gateway, Slack/Teams, Voice, Embedded BI tools) * Orchestration ...

Proton.ai

UI Product Designer

Cambridge, MA · On-site +1

$80K - $100K/yr

... the AI operating system for wholesale distribution, embedded in the workflows that move nearly ... Cambridge, MA (hybrid, 3 days a week in Harvard Square) or remote in the EU. Level : Product ...

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Remote Embedded Ai information

See Boston, MA salary details

$76K

$166.6K

$189K

How much do remote embedded ai jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote embedded ai 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 a remote embedded AI engineer?

A Remote Embedded AI engineer is a professional who develops and integrates artificial intelligence (AI) algorithms into embedded systems, such as IoT devices, sensors, or smart appliances, while working from a remote location. Their role involves optimizing AI models to run efficiently on hardware with limited resources, ensuring reliable performance and low power consumption. These engineers typically collaborate with cross-functional teams to deliver intelligent, connected products, leveraging skills in machine learning, software development, and embedded hardware. Working remotely allows them to contribute to global projects without being tied to a specific office location.

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

To thrive as a Remote Embedded AI Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++, Python, or TensorFlow Lite, often supported by a degree in computer engineering or related fields. Familiarity with real-time operating systems (RTOS), edge AI development platforms, and version control tools such as Git is typically required. Strong problem-solving skills, effective remote communication, and self-motivation help you excel in collaborative yet independent work environments. These competencies are crucial for building efficient, innovative AI solutions on hardware platforms while ensuring seamless teamwork across distributed teams.

What are some common challenges faced by remote embedded AI engineers, and how can they be overcome?

Remote Embedded AI Engineers often encounter challenges such as limited access to hardware for testing, asynchronous communication with distributed teams, and integrating AI models within resource-constrained embedded systems. Overcoming these challenges involves utilizing remote debugging tools, setting up robust simulation environments, and maintaining clear, regular communication with team members. Collaboration platforms and thorough documentation help ensure smooth coordination, while staying updated on best practices in embedded AI can address technical limitations.

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

AspectRemote Embedded AiRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in Computer Science, Electrical Engineering, or related fields; experience with embedded systemsBachelor's or higher in Computer Science, Data Science, or related fields; strong programming and statistical skills
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsCloud platforms, data centers, software development environments
Industry UsageConsumer electronics, automotive, industrial IoTTech companies, finance, healthcare, research
Common Search/ComparisonYesNo

Remote Embedded Ai professionals focus on developing AI algorithms for embedded hardware and real-time systems, often working with IoT devices and specialized hardware. In contrast, Remote Machine Learning Engineers primarily develop models in cloud environments for data analysis and prediction. While both roles require strong programming skills, Embedded Ai emphasizes hardware integration, whereas Machine Learning Engineers focus on scalable model deployment.

What are the most commonly searched types of Embedded Ai jobs in Boston, MA?

The most popular types of Embedded Ai jobs in Boston, MA are:

What are popular job titles related to Remote Embedded Ai jobs in Boston, MA?

For Remote Embedded Ai jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Remote Embedded Ai jobs in Boston, MA look for?

The top searched job categories for Remote Embedded Ai jobs in Boston, MA are:

What cities near Boston, MA are hiring for Remote Embedded Ai jobs?

Cities near Boston, MA with the most Remote Embedded Ai job openings:

Remote Embedded Ai jobs near you

Software Engineer, Embedded Systems

MatrixSpace

Burlington, MA • Remote

$150K - $185K/yr

Full-time

Re-posted 16 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.