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Internship Edge Ai Machine Learning Jobs in Georgia

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

You'll work at the intersection of machine learning and the physical world to build AI systems that learn from real industrial data and connect with the engineering models behind them. The role lives ...

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 ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

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Internship Edge Ai Machine Learning information

What is an internship edge AI machine learning?

Internship Edge AI Machine Learning positions are entry-level roles designed for students or recent graduates who want hands-on experience working with artificial intelligence and machine learning technologies, especially those related to 'edge' computing. These internships focus on developing, optimizing, and deploying AI/ML models that run on edge devices such as smartphones, IoT devices, and embedded systems, rather than in the cloud. Interns typically assist in research, data preparation, model training, and software development while gaining industry-relevant skills. These roles are ideal for individuals interested in both hardware and software aspects of AI. The experience gained can be valuable for future careers in data science, machine learning engineering, or AI research.

What are the key skills and qualifications needed to thrive as an internship edge AI machine learning professional, and why are they important?

To thrive in an Internship Edge AI Machine Learning role, you need a solid background in computer science, mathematics, and machine learning concepts, typically supported by coursework or relevant projects. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud or edge computing platforms is highly valuable. Strong analytical thinking, problem-solving abilities, and effective teamwork skills help you adapt and contribute meaningfully in collaborative research and development environments. These competencies are crucial for innovating and deploying machine learning models on edge devices, ensuring impactful real-world AI solutions.

What is the difference between Internship Edge Ai Machine Learning vs Data Analyst?

AspectInternship Edge Ai Machine LearningData Analyst
Required CredentialsRelevant coursework, basic programming skills, possibly some certificationsDegree in statistics, mathematics, or related field; proficiency in data tools
Work EnvironmentInternship setting, collaborative teams, research-focusedOffice environment, data-driven decision-making teams
Employer & Industry UsageTech companies, startups, research institutionsBusiness, finance, healthcare, marketing sectors

Internship Edge Ai Machine Learning roles typically focus on foundational skills in AI and machine learning, often as entry-level or internship positions. Data Analysts work across various industries analyzing data to inform business decisions. While both roles involve working with data, AI internships emphasize machine learning models, whereas Data Analysts focus on data interpretation and reporting.

What types of projects can I expect to work on during an internship in edge AI and machine learning?

As an intern in Edge AI and Machine Learning, you will likely work on projects that involve developing and optimizing machine learning models for deployment on edge devices such as smartphones, IoT sensors, or embedded systems. Typical tasks include data preprocessing, model training and evaluation, and implementing algorithms with resource constraints in mind. You may also collaborate with hardware engineers and software developers to ensure that your solutions run efficiently on limited hardware. This hands-on experience provides a strong foundation for understanding real-world AI deployment challenges and can open doors to more advanced roles in the future.
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Internship Edge Ai Machine Learning jobs near you
Infographic showing various Internship Edge Ai Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

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.