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Machine Learning Engineer Intern Jobs in Atlanta, GA

TriOptus LLC

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 ...

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Workday

Sr Machine Learning Engineer

Atlanta, GA · On-site

$159K - $276K/yr

... Machine Learning driven features with Python (including NumPy, SciPy, Pandas, TensorFlow, Pytorch) Other Qualifications: * Strong programming skills in Python with proficiency in relevant libraries ...

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 ...

AppFolio

Sr. Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Omaze

Staff Machine Learning Engineer - Search

Atlanta, GA · On-site

$159 - $208.95/hr

As a Staff Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will own critical production ML systems across ...

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All JobsMachine Learning Engineer Intern JobsMachine Learning Engineer Intern Jobs in Atlanta, GA

Machine Learning Engineer Intern information

See Atlanta, GA salary details

$24.5K

$41K

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

As of Aug 10, 2026, the average yearly pay for machine learning engineer intern in Atlanta, GA is $40,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,300.00 and $44,200.00 per year, depending on experience, location, and employer.

What do machine learning engineer interns do?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a machine learning engineer intern?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What skills and qualifications are needed to thrive as a machine learning engineer intern?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are the most commonly searched types of Machine Learning Engineer jobs in Atlanta, GA? The most popular types of Machine Learning Engineer jobs in Atlanta, GA are:
What are popular job titles related to Machine Learning Engineer Intern jobs in Atlanta, GA? For Machine Learning Engineer Intern jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Atlanta, GA look for? The top searched job categories for Machine Learning Engineer Intern jobs in Atlanta, GA are:
What cities near Atlanta, GA are hiring for Machine Learning Engineer Intern jobs? Cities near Atlanta, GA with the most Machine Learning Engineer Intern job openings:
Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $40,951 per year, or $19.7 per hour.

Machine Learning Engineer

TriOptus LLC

Atlanta, GA • On-site

$85.92 - $130/hr

Full-time, Contractor

Re-posted 23 days ago

Job description

  • 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 the primary MLOps expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production.
  • Candidate's focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to client's shared ML platform.
  • Candidates will work closely with cross-functional collaborators-including ML researchers, product managers, and platform engineers-to deliver scalable, reliable, and low-latency ML solutions.
  • This contract position has potential to transition into a full-time role in the future based on performance and business needs.
Key Responsibilities:
Feature Development and Delivery:
  • Design, implement, and deploy new features and enhancements to ML products, collaborating with Product and ML Research teams to refine requirements.
Technical Ownership and Stewardship:
  • Technical ownership of existing and new production ML products in your area, ensuring alignment of technical investments with business goals (in collaboration with a product owner) and engineering best practices.
  • End-to-end technical stewardship of ML products, ensuring ongoing reliability and performance.
Contribute to ML platform:
  • Contribute to the evolution of the shared ML platform alongside other MLOps engineers to drive best practices and shared tooling across all products.
Operational Excellence:
  • Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging, ensuring high operational standards.
  • Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.
Continuous Improvement:
  • Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.
Release Management:
  • Oversee pre-release testing, coordinate releases, and ensure smooth enablement of new features.
Leadership:
  • Provide technical guidance and support to other engineers and data scientists to solve complex technical challenges.
  • Mentor and coach other engineers, supporting their professional growth.
  • Foster a culture of collaboration, continuous improvement, and knowledge sharing.
Act Like an Owner:
  • Proactively identify and resolve blockers, navigate processes, and independently seek out information and connect with relevant teams to drive solutions in the face of ambiguity.
  • Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.
Experience and Skills - Required:
  • 5 plus years as an ML Engineer, MLOps Engineer, or similar, with hands-on production experience
  • Proven expertise with ML model deployment, API design, and integration into production environments
  • Strong Python programming and relevant ML/data libraries
  • Experience with containerization, orchestration, and AWS cloud services
  • Building and operating CI/CD pipelines (Jenkins preferred)
  • Experience designing and configuring low-latency databases to serve real-time features, such as DynamoDB
  • Monitoring, troubleshooting, and optimizing production ML systems
  • Pre-release testing and release management
  • Demonstrated ability to work independently, navigate ambiguity, and deliver results
  • Excellent communication skills and ability to collaborate in cross-functional teams
Experience and Skills - Preferred:
  • Experience with MLFlow, model versioning, and storage
  • Exposure to GenAI/NLP, AutoML, model explainability
  • Familiarity with Databricks or similar platforms
  • Experience supporting high-volume, real-time data products
  • Automated testing and validation frameworks
Why Join Client?
  • Impact: Play a key role as the technical owner of high-profile ML products delivering meaningful business impact to merchants and advancing key pillars of the company's strategy.
  • Candidate's work will directly influence the reliability, scalability, and evolution of critical production systems.
  • Autonomy: Take end-to-end technical ownership of candidate's product area, with the freedom and responsibility to drive technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.
  • Collaboration: Join a cross-functional, high-performing team where candidate's expertise is valued and candidate's contributions make a real difference.
Note:
  • Team: Data Science Enablement (MLOps)
  • Rate card: $85.92 - $130.00 hourly.
  • Any candidate submitted with a bill rate over $130 will be rejected.
  • Work schedule and time zone: Eastern Time 8.00 am to 5.00 pm
  • Overtime Eligible(Y/N): N
  • Workstoppage Eligible (Y/N): HM looking into this
  • Remote (Y/N): Y
  • Potential to convert and/or extend: Yes.
  • If convert, need to be located in Cincinnati OH, Atlanta GA, or Alpharetta GA (3-day onsite requirement)

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