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Mlops Machine Learning Engineer Jobs in Georgia (NOW HIRING)

innovitusa

Machine Learning Engineer

Atlanta, GA · On-site

W2 Candidates Only 🚨 We are seeking a Machine Learning Engineer to develop, deploy, and optimize ... MLOps * Experience with AI/ML production environments #Hiring #W2 #MachineLearningEngineer ...

Winixx

Machine Learning Engineer

Atlanta, GA · On-site

$130 - $185/hr

Openings › Software › Machine Learning Engineer Software Machine Learning Engineer Atlanta, US ... Familiarity with MLOps practices including model versioning, monitoring, and deployment * Strong ...

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 ... Experience with CI/CD for ML (MLOps), monitoring, and observability. * Familiarity with anomaly ...

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... Experience with CI/CD for ML (MLOps), monitoring, and observability. * Familiarity with anomaly ...

The E Group

Machine Learning Engineer

Atlanta, GA · On-site

$50 - $60/hr

Machine Learning Engineer 3 Date Posted: 7/31/26 Location: Atlanta, GA 30308 Job Type: Contract ... Work closely with MLOps, DevOps, and data engineering teams to align on infrastructure and ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD ...

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 systems of systems for training and running machine learning models with industry best practice

Equifax

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 systems of systems for training and running machine learning models with industry best practice

Speria

Machine Learning Engineer

Atlanta, GA · On-site

$120 - $160/hr

Job Summary We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team at Speria MTech. The ideal candidate will play a crucial role in designing, building, and ...

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

Machine Learning Engineer KSB GIW, Inc. Department: Engineering, Research & Development Reports to: Metallurgical and Materials R&D Lab Manager Location: Grovetown, GA, USA (onsite) Shift: First FLSA ...

Speria

Machine Learning Operations Engineer

Atlanta, GA · On-site

$120 - $180/hr

The MLOps Engineer works closely with Machine Learning Engineers and Data Engineers to ensure that models and decisioning systems are production-ready, observable, cost-efficient, and seamlessly ...

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Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

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What cities in Georgia are hiring for Mlops Machine Learning Engineer jobs?

Cities in Georgia with the most Mlops Machine Learning Engineer job openings:

Mlops Machine Learning Engineer jobs near you

Machine Learning Engineer

innovitusa

Atlanta, GA • On-site

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

🚨 Hiring: W2 Candidates Only 🚨

Job Description:
We are seeking a Machine Learning Engineer to develop, deploy, and optimize machine learning models and AI solutions. The ideal candidate will have strong experience with Python, machine learning frameworks, data processing, and cloud-based ML platforms.

Required Skills:

  • 5+ years of Machine Learning experience
  • Python
  • Scikit-learn
  • TensorFlow or PyTorch
  • Machine Learning algorithms
  • Pandas and NumPy
  • SQL
  • Model development and evaluation
  • Data preprocessing
  • Model deployment

Preferred Skills:

  • Generative AI
  • Large Language Models (LLMs)
  • NLP
  • Hugging Face
  • AWS SageMaker or Azure ML
  • MLflow
  • Docker and Kubernetes
  • MLOps
  • Experience with AI/ML production environments

#Hiring #W2 #MachineLearningEngineer #MachineLearning #AI #ArtificialIntelligence #Python #TensorFlow #PyTorch #MLOps #GenAI #LLM #TechJobs #ITJobs