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Mlops Machine Learning Engineer Jobs in Atlanta, GA

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 ...

New

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 ...

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 ...

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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 ...

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 ...

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

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 ...

New

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 ...

New

Machine Learning Engineer

Atlanta, GA · On-site

$85.92 - $130/hr

* Senior MLOps Engineer (Contractor) About the Role: * Client is seeking an experienced Senior MLOps Engineer to join client's Data Science Enablement (MLOps) team as a contractor. * Candidates will be ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do ... MLOps & Infrastructure Champion MLOps best practices: model versioning, champion/challenger ...

Senior Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do ... MLOps & Infrastructure Champion MLOps best practices: model versioning, champion/challenger ...

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Mlops Machine Learning Engineer information

See Atlanta, GA salary details

$30.3K

$123.8K

$186.1K

How much do mlops machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for mlops machine learning engineer in Atlanta, GA is $123,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $149,100.00 per year, depending on experience, location, and employer.

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.

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.

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.
What job categories do people searching Mlops Machine Learning Engineer jobs in Atlanta, GA look for? The top searched job categories for Mlops Machine Learning Engineer jobs in Atlanta, GA are:

Machine Learning Engineer

Winixx

Atlanta, GA • On-site

$130 - $185/hr

Other

PTO

Posted 2 days ago

New


Job description

Openings › Software › Machine Learning Engineer

Software

Machine Learning Engineer

Atlanta, US Remote Full-time $130,000 – $185,000

About Winixx

Winixx Inc. is a New York-based technology holding company operating a portfolio of over 30 SaaS platforms across freight, fleet management, financial infrastructure, and market intelligence. Founded with a mission to modernize fragmented and underserved industries, Winixx builds technology that removes inefficiencies, creates transparency, and puts more value in the hands of the people doing the actual work. Our flagship products include Winixx Freight, a next-generation load board with embedded instant payment; fleetOS, a comprehensive fleet management and roadside assistance platform; and Baron Meddy Financial, our financial infrastructure arm facilitating capital deployment, escrow, and M&A advisory across verticals. Winixx is headquartered in Atlanta, Georgia, with remote teams operating nationwide.

Role Summary

The Machine Learning Engineer at Winixx builds the models and data systems that power intelligent features across our platforms — from load matching optimization and dynamic pricing to predictive maintenance alerts and fraud detection. You will work at the intersection of data engineering and applied research, taking models from proof-of-concept to production.

What You'll Do

  • Design, build, and deploy machine learning models that improve core platform outcomes including load matching, pricing, and fraud detection
  • Collaborate with data engineers to build and maintain feature stores and training data pipelines
  • Implement model monitoring and retraining pipelines to maintain model performance over time
  • Work with product and engineering teams to integrate ML predictions into production systems
  • Conduct experimentation to validate model improvements using rigorous A/B testing methodology
  • Document model architectures, training procedures, and performance benchmarks
  • Evaluate and adopt new ML tools, frameworks, and techniques relevant to logistics and marketplace problems
  • Contribute to the development of Winixx's internal ML platform and infrastructure

What We're Looking For

  • 3+ years of machine learning engineering or applied research experience
  • Strong Python skills with proficiency in ML frameworks such as PyTorch, TensorFlow, or scikit-learn
  • Experience building and maintaining end-to-end ML pipelines in a production environment
  • Solid foundation in statistics, probability, and optimization
  • Experience with recommendation systems, pricing models, or anomaly detection is highly valued
  • Familiarity with MLOps practices including model versioning, monitoring, and deployment
  • Strong SQL and data manipulation skills
  • Bachelor's or Master's degree in Computer Science, Statistics, or a related quantitative field
  • Competitive base salary commensurate with experience
  • Performance bonus program tied to individual and company milestones
  • Hybrid work environment with flexible scheduling
  • Career growth opportunities across 30+ SaaS products and multiple verticals
  • Front-row seat at a technology company at the beginning of a major national expansion
  • Collaborative, mission-driven team environment
  • Paid time off and company holidays
  • Professional development and continuing education support

Winixx Inc. is an equal opportunity employer. We evaluate all applicants on the basis of qualifications, experience, and demonstrated ability without regard to race, color, religion, sex, national origin, disability, veteran status, or any other characteristic protected by applicable law.

The compensation range reflected in this posting represents the minimum and maximum target range for this position. Individual pay within the posted range is determined by a candidate's demonstrated experience, educational background, skill set, and geographic location. Final compensation is established at the time of offer and may fall anywhere within the stated range based on these factors.

Compensation ranges reflect national US market data and are subject to change. Additional forms of compensation may include performance bonuses, equity participation, and other benefits as outlined in your offer documentation.

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