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Full Time Edge Ai Machine Learning Jobs (NOW HIRING)

Honeywell

Director Embedded AI Engineering

Atlanta, GA · On-site

$126K - $166K/yr

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 ...

Huzzle

AI Engineer - Remote

Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a skilled AI ... edge AI initiatives. This is an exciting opportunity for someone passionate about machine learning ...

The Hartford

AI Machine Learning Engineer

Columbus, OH · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading AI and ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

It is a cutting-edge research and development opportunity with the potential to improve people ... Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ...

The Hartford

AI Machine Learning Engineer

Charlotte, NC · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading AI and ...

The Hartford

AI Machine Learning Engineer

Chicago, IL · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading AI and ...

The Hartford

AI Machine Learning Engineer

Hartford, CT · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading AI and ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

It is a cutting-edge research and development opportunity with the potential to improve people ... Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ...

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Full Time Edge Ai Machine Learning information

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$25.5K

$42.6K

$88K

How much do full time edge ai machine learning jobs pay per year?

As of Jul 22, 2026, the average yearly pay for full time edge ai machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are Full Time Edge AI Machine Learning jobs?

Full Time Edge AI Machine Learning jobs involve developing and deploying machine learning models that run directly on edge devices, such as smartphones, IoT devices, or embedded systems, rather than relying solely on cloud computing. Professionals in these roles work on optimizing algorithms for low-power, resource-constrained environments and enabling real-time AI processing at the device level. These jobs typically require expertise in AI, machine learning, embedded systems, and sometimes hardware integration, and are essential for applications like smart cameras, autonomous vehicles, and industrial automation.

What are the key skills and qualifications needed to thrive as a Full Time Edge AI Machine Learning Engineer, and why are they important?

To thrive as a Full Time Edge AI Machine Learning Engineer, you need a solid background in computer science, machine learning algorithms, and embedded systems, often supported by a relevant degree and experience in AI model deployment. Familiarity with frameworks like TensorFlow Lite, ONNX, and hardware platforms such as NVIDIA Jetson or ARM Cortex is typically required, along with knowledge of programming languages like Python and C++. Strong problem-solving, adaptability, and effective communication skills help you collaborate across multidisciplinary teams and address real-time deployment challenges. These combined skills ensure efficient, scalable, and robust AI solutions on resource-constrained edge devices, which is critical for success in this rapidly evolving field.

What is the difference between Full Time Edge Ai Machine Learning vs Data Scientist?

AspectFull Time Edge Ai Machine LearningData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related fields; strong programming skills
Work EnvironmentEdge devices, IoT environments, real-time data processingOffice or remote, data analysis, model development
Industry UsageAI hardware companies, IoT, autonomous systemsTech, finance, healthcare, research

Full Time Edge Ai Machine Learning specialists focus on deploying ML models on edge devices for real-time processing, often requiring knowledge of hardware and embedded systems. Data Scientists analyze data, develop models, and interpret results primarily in cloud or office settings. While both roles involve machine learning, Edge AI emphasizes deployment on hardware, whereas Data Scientists focus on data analysis and model development.

What are some common challenges faced when deploying AI models on edge devices in a full-time Edge AI Machine Learning role?

One of the main challenges in this role is optimizing machine learning models to run efficiently on resource-constrained edge devices, which often have limited processing power and memory compared to cloud environments. Ensuring low latency and real-time performance without sacrificing accuracy requires specialized techniques such as model quantization or pruning. Additionally, maintaining robust security and handling data privacy on distributed devices adds complexity. Collaboration with hardware engineers and software developers is frequently required to address these multidisciplinary challenges.
More about Full Time Edge Ai Machine Learning jobs
What cities are hiring for Full Time Edge Ai Machine Learning jobs? Cities with the most Full Time Edge Ai Machine Learning job openings:
What are the most commonly searched types of Edge Ai Machine Learning jobs? The most popular types of Edge Ai Machine Learning jobs are:
What job categories do people searching Full Time Edge Ai Machine Learning jobs look for? The top searched job categories for Full Time Edge Ai Machine Learning jobs are:
Full Time Edge Ai Machine Learning jobs near you
Infographic showing various Full Time Edge Ai Machine Learning job openings in the United States as of July 2026, with employment types broken down into 67% Full Time, 22% Part Time, and 11% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Director Embedded AI Engineering

Director Embedded AI Engineering

Honeywell

Atlanta, GA • On-site

$126K - $166K/yr

Full-time

Posted 19 days ago

Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 183 frontline employees who took The Breakroom Quiz

67th of 534 rated manufacturers

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.

What Honeywell employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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