1

Machine Learning Data Associate Jobs in Atlanta, GA

We aim to create software that delivers real-time data to the entire supply chain that allows ... Job Summary We are seeking a highly skilled and motivated Machine Learning Operations (MLOps ...

Analyzes complex data sets to solve real-world business and customer use cases. * Performs end-to-end development of machine learning models * May assist with or lead the development of industry ...

Analyzes complex data sets to solve real-world business and customer use cases. * Performs end-to-end development of machine learning models * May assist with or lead the development of industry ...

Analyzes complex data sets to solve real-world business and customer use cases. * Performs end-to-end development of machine learning models * May assist with or lead the development of industry ...

Analyzes complex data sets to solve real-world business and customer use cases. * Performs end-to-end development of machine learning models * May assist with or lead the development of industry ...

Analyzes complex data sets to solve real-world business and customer use cases. * Performs end-to-end development of machine learning models * May assist with or lead the development of industry ...

Analyzes complex data sets to solve real-world business and customer use cases. * Performs end-to-end development of machine learning models * May assist with or lead the development of industry ...

Showing results 41-60

Machine Learning Data Associate information

See Atlanta, GA salary details

$9

$18

$29

How much do machine learning data associate jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for machine learning data associate in Atlanta, GA is $18.02, according to ZipRecruiter salary data. Most workers in this role earn between $14.81 and $19.18 per hour, depending on experience, location, and employer.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities near Atlanta, GA are hiring for Machine Learning Data Associate jobs?

Cities near Atlanta, GA with the most Machine Learning Data Associate job openings:

Infographic showing various Machine Learning Data Associate job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $37,480 per year, or $18 per hour.

Machine Learning Lead Engineer

Cox Automotive

Powder Springs, GA • On-site

$134K - $224K/yr

Full-time

PTO

Re-posted 17 days ago


Cox Automotive rating

7.8

Company rating: 7.8 out of 10

Based on 143 frontline employees who took The Breakroom Quiz

99th of 151 rated financial services


Job description

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting-edge research with the responsibility of building a culture of continuous learning and knowledge sharing. You'll lead efforts to identify, evaluate, and prototype emerging ML technologies while establishing our company as a thought leader in the ML community. Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and improve data quality. Structures, trains, and deploys models to learn from complex data across multiple modalities (e.g., structured, unstructured, image, video, audio) to uncover patterns and develop practical solutions. Possesses deep knowledge in at least one sub-area of machine learning, such as deep learning, generative AI, computer vision, optimization, predictive models, or causal machine learning.
WHAT YOU'LL DO
Key Responsibilities
  • Accelerate ML development using AI tools for code generation, feature engineering, optimization, and validation
  • Stay up to date with advancements in ML, AI, and emerging technologies
  • Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference
  • Optimize model performance, scalability, and reliability in production environments
  • Collaborate cross-functionally to translate model insights into business value and communicate project updates
  • Contribute to ML infrastructure improvements, best practices, and documentation
  • Partner with engineering teams to integrate AI-enhanced models and establish automated monitoring frameworks.
  • Establish AI governance practices including bias detection, interpretability, compliance monitoring, and responsible deployment.
  • Mentor teams in AI adoption, share best practices, and promote responsible AI innovation culture.
  • Lead AI transformation initiatives including tool evaluation, governance development, and strategic adoption planning.
  • Analyzes complex data sets to solve real-world business and customer use cases.
  • Performs end-to-end development of machine learning models
  • May assist with or lead the development of industry whitepapers or other technical publications.
  • Continuously evaluate AI processes for accuracy, efficiency, and business impact while staying current on emerging technologies.
  • Design agentic workflows for autonomous training, data pipelines, and analytical problem solving appropriate to experience level.

Key AI Use Cases
  • AI-Accelerated Model Development: Use GitHub Copilot, Claude Code for rapid ML prototyping, automated feature engineering, and intelligent hyperparameter optimization.
  • Agentic ML Workflows: Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training pipelines, multi-step analysis, and collaborative research.
  • AI-Enhanced Model Interpretation: Build on traditional frameworks (SHAP, LIME) with AI tools for enhanced stakeholder communication and automated insights.
  • AI-Powered Research: Leverage manual/autonomous competitive intelligence and research acceleration tools for methodology discovery and algorithm innovation.

WHO YOU ARE
Required Skills
  • Proficiency in AI development tools (GitHub Copilot, Claude, GPT-4) for ML development with ability to validate AI outputs for production readiness.
  • Understanding of agentic frameworks (AWS AgentSquad, AWS Strands, LangChain, agent patterns) with progression from basic configuration to custom enterprise system design.
  • Knowledge of AI ethics, responsible AI practices, and governance frameworks for business-critical ML deployment.
  • Ability to leverage AI like Co-Pilot for technical communication to stakeholders and cross-functional collaboration.
  • Commitment to continuous learning in AI-augmented data science and responsible AI use.

Required Qualifications
  • Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in future.
  • Bachelor's degree in a related discipline and 6 years' experience in Machine Learning; or a different combination, such as a master's degree and 4 years' experience; a Ph.D. and 1 years' experience in a related field; or 18 years' experience in a related field with no degree
  • Minimum of 6 years of experience as a Machine Learning Engineer or equivalent
  • Deep expertise in multiple ML domains and familiarity with emerging research areas
  • Strong experience in technology evaluation, competitive analysis, and strategic planning
  • Comfortability with non-deterministic systems
  • Product background- understand how to prioritize, collaborate across teams, manage dependencies with others, set strategy
  • Experience in Rally, Jira or similar tools
  • Skilled in analytical thinking, consulting, requirements analysis, system and technology integration and technology savvy.
  • Skilled in collaborating with intent, communicating with impact, developing trust, driving innovation and striving for excellence.
  • Proven track record of leading innovative projects from concept to proof-of-concept
  • Demonstrated success in knowledge sharing and thought leadership (publications, speaking, etc.)
  • Experience building and leading high-performing research or innovation teams
  • Excellent communication skills for technical and executive audiences
  • Strong network within the ML research community
  • Experience with research collaboration and partnership development
  • Other duties as needed or required
  • Must be comfortable with change and an evolving environment

Preferred Qualifications
  • Experience in corporate research labs, innovation teams, or technology consulting
  • Track record of identifying and successfully implementing breakthrough technologies
  • Background in technology transfer from research to business applications
  • Strong presence in the ML community (conference speaking, open-source contributions, etc.)
  • Knowledge of emerging areas such as LLMs, Agents, foundation models, multimodal AI, or quantum ML

Leadership Expectations
  • Foster a culture of experimentation, learning, and calculated risk-taking
  • Drive consensus on research priorities while maintaining innovation velocity
  • Develop talent through mentoring in both technical skills and research methodologies
  • Communicate complex experimental results and strategic implications to all organizational levels
  • Lead by example in intellectual curiosity, scientific rigor, and knowledge sharing
  • Build bridges between cutting-edge research and practical business applications
  • Establish the team as a recognized center of excellence in experimental ML

USD 134,900.00 - 224,900.00 per year
Compensation:
Compensation includes a base salary in the range of $134,900.00 - $224,900.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.
Benefits:
The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.
EOE, including disability/vets

What Cox Automotive employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Cox Automotive logo

About Cox Automotive

Sourced by ZipRecruiter

At Cox Automotive, people of every background are driven by their passion for mobility, innovation and community. We transform the way the world buys, sells, owns and uses cars, accelerating the industry with global powerhouse brands like Autotrader, Kelley Blue Book, Manheim and more. What's more, we do it all with an emphasis on employee growth and happiness. Drive your future forward and join Cox Automotive today! Cox empowers employees to build a better future and has been doing so for over 120 years. With exciting investments and innovations across transportation, communications, cleantech and healthcare, our family of businesses - which includes Cox Automotive and Cox Communications - is forging a better future for us all. Ready to make your mark? Join us today! Benefits of working at Cox may include health care insurance (medical, dental, vision), retirement planning (401(k)), and paid days off (sick leave, parental leave, flexible vacation/wellness days, and/or PTO). For more details on what benefits you may be offered, visit our benefits page . Cox is an Equal Employment Opportunity employer - All qualified applicants/employees will receive consideration for employment without regard to that individual's age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law. Cox provides reasonable accommodations when requested by a qualified applicant or employee with disability, unless such accommodations would cause an undue hardship. Statement to ALL Third-Party Agencies and Similar Organizations: Cox accepts resumes only from agencies with which we formally engage their services. Please do not forward resumes to our applicant tracking system, Cox employees, Cox hiring manager, or send to any Cox facility. Cox is not responsible for any fees or charges associated with unsolicited resumes.

Industry

Automobile dealers and technology, communication and media

Company size

5,001 - 10,000 Employees

Headquarters location

Atlanta, GA, US