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Manager Edge Ai Machine Learning Jobs in Georgia

Role Overview We are seeking a Senior Staff AI / Machine Learning Architect to serve as a key ... in edge ML and NPU enabled platforms-while collaborating closely with researchers, software ...

Role Overview We are seeking a Senior Staff AI / Machine Learning Architect to serve as a key ... Partner with platform managers and engineering teams to integrate ML models into shipped products ...

Role Overview We are seeking a Senior Staff AI / Machine Learning Architect to serve as a key ... Partner with platform managers and engineering teams to integrate ML models into shipped products ...

Metallurgical and Materials R&D Lab Manager Location: Grovetown, GA, USA (onsite) Shift: First FLSA ... You'll work at the intersection of machine learning and the physical world to build AI systems that ...

This role combines technical leadership in cutting-edge research with the responsibility of ... Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems ...

AI/ML coursework preferred * 7+ years of related work experience, including proven experience ... Technical Leadership - Be able to lead and manage a team of machine learning engineers, data ...

... AI systems for enterprise spend management and risk controls. The ideal candidate has a strong ... edge applied research in agentic AI. Key Responsibilities * Contribute to the design, training ...

This role combines technical leadership in cutting-edge research with the responsibility of ... Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems ...

This role combines technical leadership in cutting-edge research with the responsibility of ... Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems ...

Showing results 21-40

Manager Edge Ai Machine Learning information

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

AspectManager Edge Ai Machine LearningData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; certifications in AI/MLBachelor's or Master's in Data Science, Statistics, Computer Science; often certifications in data analysis or ML
Work EnvironmentLeads teams, manages projects, collaborates with stakeholders in AI/ML applicationsAnalyzes data, develops models, and provides insights, often working independently or in teams
Employer & Industry UsageTech companies, AI startups, enterprises implementing AI solutionsResearch institutions, tech firms, finance, healthcare, and other data-driven industries

While both roles involve AI and machine learning, the Manager Edge Ai Machine Learning focuses on leading teams and managing AI projects, whereas Data Scientists primarily analyze data and develop models. The manager role emphasizes leadership and project oversight, while Data Scientists concentrate on technical analysis and model development.

What are the most commonly searched types of Edge Ai Machine Learning jobs in Georgia?

The most popular types of Edge Ai Machine Learning jobs in Georgia are:

What cities in Georgia are hiring for Manager Edge Ai Machine Learning jobs?

Cities in Georgia with the most Manager Edge Ai Machine Learning job openings:

Infographic showing various Manager Edge Ai Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.

Other

Posted 7 days ago


Job description

AI Product Manager
Atlanta ,GA ( Need only Local Candidates) - Onsite
Contract
ROLE_DESCRIPTION:
• Bachelor's degree in Computer Science, Engineering, Information Systems, Business, or a related field.
• 8+ years of experience in Product Management, Program Management, or Digital Product Development.
• 3+ years of experience working with AI, Machine Learning, Analytics, or Data-driven products.
• Strong understanding of Agile methodologies and product management best practices.
• Experience working with cross-functional teams in fast-paced environments.
• Excellent communication, stakeholder management, and leadership skills.