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Edge Ai Machine Learning Jobs in Atlanta, GA (NOW HIRING)

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

$120 - $165/hr

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... You will work closely with AI/ML researchers, data engineers, and product teams to design ...

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... edge applied research in agentic AI. Key Responsibilities * Contribute to the design, training ...

Equifax, Inc.

Machine Learning Engineer

Atlanta, GA · On-site

Equifax is excited to add a Machine Learning Engineer to our team. What you'll do * Design complex ... AI/ML coursework preferred * 7+ years of related work experience, including proven experience ...

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All JobsEdge Ai Machine Learning JobsEdge Ai Machine Learning Jobs in Atlanta, GA

Edge Ai Machine Learning information

See Atlanta, GA salary details

$24.5K

$41K

$84.6K

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

As of Aug 8, 2026, the average yearly pay for edge ai machine learning in Atlanta, GA is $40,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,300.00 and $44,200.00 per year, depending on experience, location, and employer.

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

How to become an edge AI machine learning engineer?

To become an edge AI machine learning engineer, develop strong skills in machine learning, embedded systems, and programming languages like Python and C++. Gain experience with hardware platforms such as NVIDIA Jetson or Raspberry Pi, and learn to optimize models for low-power, resource-constrained environments. Earning certifications in AI, embedded systems, or IoT can also enhance your qualifications.
What are the most commonly searched types of Edge Ai Machine Learning jobs in Atlanta, GA? The most popular types of Edge Ai Machine Learning jobs in Atlanta, GA are:
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What cities near Atlanta, GA are hiring for Edge Ai Machine Learning jobs? Cities near Atlanta, GA with the most Edge Ai Machine Learning job openings:
Edge Ai Machine Learning jobs near you
Infographic showing various Edge Ai Machine Learning job openings in Atlanta, GA as of August 2026, with employment types broken down into 5% Internship, 79% Full Time, and 16% Contract. Highlights an 90% In-person, 5% Hybrid, and 5% Remote job distribution, with an average salary of $40,951 per year, or $19.7 per hour.

Solution Architect IV AI & Automation 4P/789

4P Consulting Inc.

Atlanta, GA • On-site

$60.75 - $80/hr

Contractor

Posted 8 days ago

Job description

Position: Solution Architect IV – AI & Automation

Location: Atlanta, GA
Duration: 5 Months

Client: Southern Company Services

Southern Company Services is seeking an experienced Solution Architect IV to lead the design, development, and production deployment of enterprise AI, machine learning, automation, and agentic AI solutions.

This role combines architecture leadership with hands-on engineering. The ideal candidate will define technical standards, build production-grade solutions, guide engineering teams, and ensure systems meet enterprise requirements for security, scalability, compliance, responsible AI, observability, and operational support.

Key Responsibilities

· Design enterprise AI, machine learning, automation, and agentic AI solutions.

· Develop architectures for LLM applications, AI agents, RAG solutions, vector databases, APIs, and enterprise integrations.

· Build and support production-grade software solutions and reusable technical components.

· Lead architecture reviews and provide technical direction to engineering teams.

· Partner with product, engineering, cloud, data, cybersecurity, and business stakeholders.

· Create solution designs, technical specifications, implementation plans, and engineering standards.

· Support delivery planning, work allocation, risk management, and production escalations.

· Ensure solutions align with enterprise security, governance, compliance, scalability, reliability, and observability standards.

Required Qualifications

· 10+ years of experience in solution architecture, software engineering, or enterprise architecture.

· Experience leading enterprise AI, machine learning, automation, or agentic AI initiatives from design through deployment.

· Strong expertise in LLMs, AI agent frameworks, RAG, vector databases, APIs, cloud platforms, and enterprise integration.

· Hands-on experience designing and building scalable, production-grade applications.

· Experience leading technical teams and conducting architecture reviews.

· Strong understanding of responsible AI, cybersecurity, compliance, observability, and operational-support models.

· Strong communication, leadership, and problem-solving skills.

Preferred Qualifications

· Experience with Azure, AWS, or Google Cloud Platform.

· Familiarity with containers, Kubernetes, microservices, CI/CD, and API management.

· Experience with AI governance, model evaluation, monitoring, logging, and performance optimization.

· Utility, energy, or regulated-industry experience is preferred.