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Manager Edge Ai Machine Learning Jobs in Tennessee

Deloitte

Senior AI Engineer - SFL Scientific

Nashville, TN

$100K - $138K/yr

... machine learning engineers, project managers, and industry experts to develop robust AI ... edge AI, and renewable energy. Key responsibilities: * Work with clients to design, develop, and ...

Crowe LLP

Machine Learning Engineer

Knoxville, TN · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

New

Crowe LLP

Machine Learning Engineer

Nashville, TN

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

New

Covenant Health

AI SPECIALIST

Knoxville, TN

$15.50 - $20.50/hr

AI Specialist, IT Care Management Support Full Time, 80 Hours Per Pay Period, Day shift Covenant ... Develop and tests machine learning models and algorithms tailored to healthcare and business ...

Covenant Health

AI SPECIALIST

Knoxville, TN · On-site

$15.50 - $20.50/hr

Overview AI Specialist, IT Care Management Support Full Time, 80 Hours Per Pay Period, Day shift ... Develop and tests machine learning models and algorithms tailored to healthcare and business ...

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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.

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Infographic showing various Manager Edge Ai Machine Learning job openings in Tennessee as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Memphis, TN • On-site

Other

Re-posted 27 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply