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Embedded Ai Engineer Jobs in Georgia (NOW HIRING)

Honeywell

Director Embedded AI Engineering

Atlanta, GA · On-site

$126.60K - $166.50K/yr

We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and ... Advanced degree in Computer Science, Electrical Engineering, or related technical field preferred.

Dlapiper

AI Solutions Engineer

Atlanta, GA · Hybrid

Summary The AI Solutions Engineer is an embedded partner to the Professional Excellence (PE) Practice Group, responsible for intake and shaping of demand into clear problem statements, prioritized ...

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$59.1K

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$146.9K

How much do embedded ai engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for embedded ai engineer in Georgia is $129,514.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $146,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Embedded AI Engineer, and why are they important?

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 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 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 Georgia? For Embedded Ai Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Embedded Ai Engineer jobs in Georgia look for? The top searched job categories for Embedded Ai Engineer jobs in Georgia are:
What cities in Georgia are hiring for Embedded Ai Engineer jobs? Cities in Georgia with the most Embedded Ai Engineer job openings:
Embedded Ai Engineer jobs near you
Director Embedded AI Engineering

Director Embedded AI Engineering

Honeywell

Atlanta, GA • On-site

$126.60K - $166.50K/yr

Full-time

Posted 25 days ago

Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 177 frontline employees who took The Breakroom Quiz

62nd of 511 rated manufacturers

Job description

Job Description
This role is for a hands-on lead specializing in Edge AI deployment. The successful candidate will provide specialized expertise in model optimization at the edge, robust deployment, and MLOps pipeline development. You will leverage your skills in edge optimization, system and embedded knowledge, AI/machine learning, MLOps, computer vision, innovation, and problem solving to drive advanced AI solutions.
We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and strong system solution knowledge for AI application deployment.
You will be part of the Forge and AI team, based in Atlanta, Georgia.
Responsibilities
KEY RESPONSIBILITIES
  • Lead hands-on development and deployment of Edge AI solutions with a focus on model optimization and performance on embedded platforms.
  • Design and implement robust MLOps pipelines to support continuous integration and deployment of AI models at the edge.
  • Collaborate with cross-functional teams to integrate AI applications into embedded systems using GPUs and AI accelerators.
  • Provide technical leadership and mentorship in embedded AI, system architecture, and AI deployment strategies.
  • Drive innovation and problem-solving initiatives to enhance AI capabilities and deployment robustness on edge devices.

Qualifications
YOU MUST HAVE
  • Proven experience in embedded AI with hands-on expertise in GPU or AI accelerator deployment.
  • Strong skills in edge model optimization and embedded system architecture.
  • Deep understanding of AI/machine learning algorithms and computer vision applications.
  • Experience building and managing MLOps pipelines for AI model deployment at the edge.
  • Excellent problem-solving skills and a passion for innovation in embedded AI technologies.

WE VALUE
  • Background in system solutions with AI application deployment experience.
  • Strong knowledge of embedded systems and real-time operating environments.
  • Experience working in collaborative, agile environments.
  • Advanced degree in Computer Science, Electrical Engineering, or related technical field preferred.

US PERSON REQUIREMENTS:
  • Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person which is defined as a U.S. citizen, a U.S. permanent resident, or have protected status In the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

About Us
Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments - powered by our Honeywell Forge software - that help make the world smarter, safer and more sustainable.

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About Honeywell

Sourced by ZipRecruiter

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell. The Chief Architect for Honeywell Connected Enterprise will lead a team of architects and system engineers responsible for the design of applications and infrastructure that deliver high value outcomes for customers in industrial, buildings, distribution centers, and aerospace vertical markets. The Chief Architect will work directly with leadership, development teams, and offering management to design well integrated solutions that utilize software platforming to encourage reuse and speed to market.

Industry

Furniture manufacturing

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1906

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