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Manager Mlops Engineer Jobs in Georgia (NOW HIRING)

Neshent Technologies

MLOps Technical Architect

Decatur, GA · On-site

$63.25 - $76.25/hr

Strong programming experience in Python and Java. * Hands-on experience with Agentic AI frameworks ... Proficiency with GitHub for source control and version management. * Experience in model ...

Neshent Technologies

MLOps Technical Architect

Atlanta, GA · On-site

$63.75 - $77/hr

Strong programming experience in Python and Java. * Hands-on experience with Agentic AI frameworks ... Proficiency with GitHub for source control and version management. * Experience in model ...

Neshent Technologies

MLOps Technical Architect

Scottdale, GA · On-site

$64.75 - $78.25/hr

Strong programming experience in Python and Java. * Hands-on experience with Agentic AI frameworks ... Proficiency with GitHub for source control and version management. * Experience in model ...

smart folks inc

Lead AI/ML Engineer

Atlanta, GA · On-site

$98K - $129K/yr

Hands-on MLOps Experience: Proven experience building and managing CI/CD pipelines and MLOps ... engineers into tech leads. Best Regards, Srinivas Email: srinivas@smartfolksinc.com

Worldpay

Senior ML Software Engineer

Atlanta, GA · On-site

$117K - $155K/yr

Release Management: * Oversee pre-release testing, coordinate releases and ensure smooth enablement ... What you'll bring * 5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or ...

The E Group

Be Seen First

Machine Learning Engineer

Atlanta, GA · On-site

$50 - $60/hr

Work closely with MLOps, DevOps, and data engineering teams to align on infrastructure and ... Our recruiters are experts in knowing what the client manager is looking for in a resume, what bill ...

FAVARH

AI Principal Engineer

Atlanta, GA · On-site +1

The AI Principal Engineer (IC Director) is responsible for leading the design, development, and ... Deep understanding of model lifecycle management, MLOps practices, and production reliability ...

Juvare

$125K - $160K/yr

Experience supporting AI/MLOps workflows is a plus. Location * Atlanta / Remote Must Have * Cloud ... Operational experience with managed databases (backup/restore, replication, performance, and access ...

Juvare

Senior DevOps Engineer

Atlanta, GA · On-site +1

$125K - $160K/yr

Experience supporting AI/MLOps workflows is a plus. Location * Atlanta / Remote Must Have * Cloud ... Operational experience with managed databases (backup/restore, replication, performance, and access ...

JR Software Solutions, Inc.

AI/ML Engineer

Atlanta, GA · On-site +1

As an AI/ML Engineer, you'll join a collaborative team of technologists, data scientists, and ... MLOps practices, including model training, deployment, monitoring, and lifecycle management using ...

Juvare

Senior DevOps Engineer

Atlanta, GA · On-site +1

$125K - $160K/yr

Experience supporting AI/MLOps workflows is a plus. Location * Atlanta / Remote Must Have * Cloud ... Operational experience with managed databases (backup/restore, replication, performance, and access ...

Purple Drive

AI/ML Engineer

Atlanta, GA

$110K - $132K/yr

MLOps Implementation: Establish CI/CD workflows, model versioning, monitoring,and automated ... Deploy and manage AI workloads using Kubernetes (EKS), Docker, and CI/CDpipelineSenior Data ...

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Manager Mlops Engineer information

What is the difference between Manager Mlops Engineer vs Data Scientist?

AspectManager Mlops EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with MLOps toolsDegree in Data Science, Statistics, or related; proficiency in programming and analytics
Work EnvironmentCollaborates with engineering and operations teams to deploy ML modelsAnalyzes data, builds models, and interprets results for business insights
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsCommon across tech, marketing, research for data analysis and modeling

The Manager Mlops Engineer focuses on deploying and maintaining machine learning models in production environments, overseeing MLOps pipelines. In contrast, Data Scientists primarily analyze data and develop models for insights. Both roles require technical skills but differ in their focus on deployment versus analysis.

What are the most commonly searched types of Mlops Engineer jobs in Georgia? The most popular types of Mlops Engineer jobs in Georgia are:
What are popular job titles related to Manager Mlops Engineer jobs in Georgia? For Manager Mlops Engineer jobs in Georgia, the most frequently searched job titles are:
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Manager Mlops Engineer jobs near you

MLOps Technical Architect

Neshent Technologies

Decatur, GA • On-site

$63.25 - $76.25/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

We are seeking an experienced MLOps Technical Architect to lead the architecture, design, and deployment of enterprise AI/ML, Generative AI, and Agentic AI solutions. The ideal candidate will have strong expertise in MLOps, cloud-native AI platforms, LLMs, RAG architectures, and AI agent frameworks, with the ability to deliver scalable, production-ready AI solutions.

Required Skills Technical Skills
  • Strong programming experience in Python and Java.
  • Hands-on experience with Agentic AI frameworks, including Google ADK, A2A, LangChain/LangGraph, CrewAI, Semantic Kernel/AutoGen, and OpenAI Agent SDK.
  • Experience integrating Gemini Tools and Custom MCP (Model Context Protocol) Tools.
  • Strong knowledge of TensorFlow, PyTorch, and AutoML for machine learning model development.
  • Hands-on experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Natural Language Processing (NLP).
  • Experience designing and implementing RAG architectures, including data ingestion, retrieval, hybrid search, and response generation.
  • Strong experience with Google Cloud Platform (GCP), Vertex AI, and Kubeflow.
  • Experience in data preprocessing, feature engineering, and ML pipeline development.
  • Proficiency with GitHub for source control and version management.
  • Experience in model development, testing, validation, deployment, and monitoring.
  • Strong knowledge of databases including Oracle, DB2, PostgreSQL, BigQuery, Cassandra, and Big Data platforms.
  • Experience working in Agile/Scrum environments.
Good to Have
  • GPU programming and performance optimization.
  • GPU profiling and TensorRT optimization.
  • Experience with vector databases and AI model optimization techniques.
Functional Skills
  • Experience working with clients in the Retail domain.
  • Knowledge of Retail Pricing processes and merchandising solutions is an advantage.
Roles and Responsibilities
  • Collaborate with business and IT stakeholders to understand business requirements and identify AI/ML opportunities.
  • Architect scalable AI/ML, MLOps, Generative AI, and Agentic AI solutions.
  • Lead the design and development of machine learning models, AI pipelines, and intelligent agent workflows.
  • Develop, optimize, and automate ML models, pipelines, and orchestration logic.
  • Design and deploy LLM-powered applications, RAG pipelines, AI agents, and vector-based memory systems.
  • Build integrations with enterprise systems using APIs, Gemini tools, and MCP-based integrations.
  • Work closely with Data Scientists, ML Engineers, DevOps, and Software Engineering teams to ensure successful deployment and operational excellence.
  • Drive technical architecture, infrastructure, tooling, and cloud strategy for AI platforms.
  • Monitor solution performance, troubleshoot production issues, and implement continuous improvements.
  • Provide timely project updates, technical guidance, and documentation to stakeholders and leadership.
  • Identify opportunities for process automation and operational efficiency.
  • Foster collaboration across cross-functional teams to ensure successful project delivery.
Preferred Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Experience designing enterprise-scale AI/ML and MLOps platforms.
  • Familiarity with cloud-native AI deployment and CI/CD practices for machine learning.

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