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Embedded Ai Engineer Jobs in Massachusetts (NOW HIRING)

Crowe LLP

Senior AI Engineer

Boston, MA · On-site +1

$113K - $155K/yr

Senior AI Engineer 1 About Crowe Studio Crowe Studio is a business unit dedicated to helping ... innovation, embedded AI capabilities, and global delivery resources-all in service of solving ...

Socket.dev

Senior Embedded Software Engineer

Boston, MA · On-site

$140 - $160/hr

Working at the intersection of embedded hardware, edge AI, computer vision, and Linux systems, you ... This role is ideal for an engineer who enjoys rapidly prototyping solutions, working close to the ...

Socket.dev

AI Engineer

Mansfield, MA · On-site

$190 - $210/hr

You will make an impact The Principal AI Engineer is primarily responsible for the design, implementation, and support of AI-powered and agentic capabilities embedded in the company's elluminate ...

New

The Brattle Group

Data and AI Engineer

Boston, MA · On-site

$124K - $149K/yr

The Data & AI Engineering team is a specialized technical group embedded within Brattle's consulting staff. The team supports client work while also serving as an applied R&D function for the firm ...

The Brattle Group

Data and AI Engineer

Boston, MA · On-site

$124K - $149K/yr

The Data & AI Engineering team is a specialized technical group embedded within Brattle's consulting staff. The team supports client work while also serving as an applied R&D function for the firm ...

Dechert LLP

AI Engineer - Boston

Boston, MA · On-site

$140 - $175/hr

The AI Engineer is embedded within the Dechert Innovation Laband works directly with attorneys, legal professionals, and business-servicesteams to discover, evaluate, prototype, and pilot emerging AI ...

New

Tulip Interfaces

Applied AI 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 ...

Tulip Interfaces

Applied AI 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 ...

Edison

Forward Deployed AI Engineer

Boston, MA · On-site

$140 - $180/hr

Role As a Forward Deployed AI Engineer , you'll be embedded directly with leading scientific R&D organizations across pharma and biotech - taking full ownership of how Edison's AI agents create value ...

New

Tulip Interfaces

Applied AI 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 1-20

All JobsEmbedded Ai Engineer JobsEmbedded Ai Engineer Jobs in Massachusetts

Embedded Ai Engineer information

See Massachusetts salary details

$76.4K

$167.5K

$190K

How much do embedded ai engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for embedded ai engineer in Massachusetts is $167,514.00, according to ZipRecruiter salary data. Most workers in this role earn between $143,600.00 and $188,900.00 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 are popular job titles related to Embedded Ai Engineer jobs in Massachusetts?

For Embedded Ai Engineer jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Embedded Ai Engineer jobs in Massachusetts look for?

The top searched job categories for Embedded Ai Engineer jobs in Massachusetts are:

What cities in Massachusetts are hiring for Embedded Ai Engineer jobs?

Cities in Massachusetts with the most Embedded Ai Engineer job openings:

Embedded Ai Engineer jobs near you
Infographic showing various Embedded Ai Engineer job openings in Massachusetts as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $167,514 per year, or $80.5 per hour.

AI Engineer

Trinity Technology Solutions

Burlington, MA • On-site

Full-time

Re-posted 14 days ago

Job description

What You’ll Do:

  • Spearhead full-stack data & ML pipelines for sensor, video, and telemetry data powering real-time robotics and vision systems.
  • Design scalable infrastructure with strong foundations-schema, lineage, validation, and anomaly detection for embedded AI.
  • Integrate edge intelligence, observability, & feedback loops into robotics and perception.
  • Set technical standards, mentor talent, and align architecture to real-world product goals.
 

Valued Experience:

  • 10+ years driving data infra, ML systems, or end-to-end AI engineering at scale.
  • Hands-on with orchestration tools, feature stores, and cloud infra (AWS, GCP, Azure).
  • Deep software engineering skills (Python, Scala, Java) & streaming frameworks (Spark, Flink).
  • Background with robotics, CV data, and edge deployment preferred.
  • Be the visionary who delivers intelligence to robots at scale. Apply today-Lead and Build tomorrow’s physical AI.
 
  • Hands-on and Strategic software architecture and software development expertise for a Physical product-robotics or Industrial automation.
  • Thrive in a highly dynamic growth stage company! 
  • Experience with Large industrial robotics/industrial automation/manufacturing of interest