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Machine Learning Data Associate Jobs in Virginia

Refine data collection processes and improve data quality. * Design and develop scalable machine learning solutions for various applications. * Work with software developers to integrate machine ...

Refine data collection processes and improve data quality. * Design and develop scalable machine learning solutions for various applications. * Work with software developers to integrate machine ...

Implement and maintain data pipelines to support machine learning workflows. * Evaluate the effectiveness of machine learning models using appropriate metrics and validation techniques. * Document ...

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

Implement and maintain data pipelines to support machine learning workflows. * Evaluate the effectiveness of machine learning models using appropriate metrics and validation techniques. * Document ...

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Machine Learning Data Associate information

See Virginia salary details

$9

$18

$30

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

As of May 30, 2026, the average hourly pay for machine learning data associate in Virginia is $18.58, according to ZipRecruiter salary data. Most workers in this role earn between $15.24 and $19.76 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Data Associate, and why are they important?

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 are Machine Learning Data Associates?

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 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.

What cities in Virginia are hiring for Machine Learning Data Associate jobs? Cities in Virginia with the most Machine Learning Data Associate job openings:
Infographic showing various Machine Learning Data Associate job openings in Virginia as of May 2026, with employment types broken down into 76% Full Time, 23% Part Time, and 1% Contract. Highlights an 96% Physical, 3% Hybrid, and 1% Remote job distribution, with an average salary of $38,640 per year, or $18.6 per hour.
Machine Learning Engineer, Data & Machine Learning (DML)

Machine Learning Engineer, Data & Machine Learning (DML)

Amazon

Arlington, VA • On-site, Remote

$131.70K - $158.20K/yr

Full-time

Posted 14 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,788 frontline employees who took The Breakroom Quiz

7th of 39 rated national retailers


Job description

This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance.
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Machine Learning Engineer to join our team at Amazon Web Services (AWS). Are you looking to work at the forefront of Machine Learning and AI.

Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact. In this role, you'll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their AI transformation journey, providing deep expertise in machine learning, generative AI, and best practices throughout the project lifecycle.


As a Machine Learning Engineer within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You'll help customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, and define paths to navigate technical or business challenges. Working closely with stakeholders, you'll assess current data infrastructure, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale.

You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives.

Our team provides a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance.


Key job responsibilities
Key job responsibilities
Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases
Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments and optimizing for performance at scale
Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose effective strategies for implementing machine learning and generative AI solutions
Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshooting throughout project delivery and ensuring adherence to best practices
Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, and innovative approaches to leveraging diverse data sources for maximum business impact
Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts, and working with team members to prototype new technologies and evaluate technical feasibility
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.


Why AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony.

Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious.

Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
Mentorship and Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.


What Amazon employees say

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Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US