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Ml Data Associate Jobs in Washington (NOW HIRING)

Press Ganey

ML Data Scientist III

Washington, DC · On-site

$100 - $140/hr

Company DescriptionPress Ganey is the leading experience measurement, data analytics, and insights ... Press Ganey Associates LLC is an Equal Employment Opportunity/Affirmative Action employer and well ...

Leidos

Data Scientist

Fort George G Meade, MD · On-site

$107K - $195K/yr

Associate's degree with 12 years of relevant experience may be considered. * Other degrees with strong coursework in advanced math, statistics, AI/ML, computer science, or data mining, or relevant ...

Leidos

Data Scientist

Fort George G Meade, MD · On-site

$107K - $195K/yr

Associate's degree with 12 years of relevant experience may be considered. * Other degrees with strong coursework in advanced math, statistics, AI/ML, computer science, or data mining, or relevant ...

Innodata Inc.

Data & Annotation Engineer

Washington, DC

$55 - $60/hr

Associate DataCard provenance records with annotated and synthetic outputs in coordination with the ... Evaluation design for AI/ML training data: IAA methodology, drift detection, model performance ...

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All JobsMl Data Associate JobsMl Data Associate Jobs in Washington

Ml Data Associate information

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$65.1K

$77.1K

$146.1K

How much do ml data associate jobs pay per year?

As of Aug 29, 2026, the average yearly pay for ml data associate in Washington is $77,061.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,800.00 and $67,400.00 per year, depending on experience, location, and employer.

What is an ml data associate?

ML Data Associates are professionals who support machine learning projects by preparing, labeling, and validating data used to train and evaluate algorithms. They often work with large datasets, ensuring data quality and accuracy, and may use specialized tools to annotate images, text, or audio. Their work is essential for enabling machine learning models to learn from high-quality, well-structured data, and they often collaborate with data scientists and engineers to optimize data pipelines.

What are the key skills and qualifications needed to thrive as an ml data associate?

To thrive as an ML Data Associate, you need strong analytical skills, attention to detail, and a solid understanding of data annotation or labeling, often supported by a degree in a technical field. Familiarity with data labeling tools, basic programming (such as Python), and experience working with machine learning platforms are typically required. Excellent communication, problem-solving abilities, and the capacity to work efficiently in teams are important soft skills. These skills ensure high-quality, accurately labeled datasets that are essential for training effective machine learning models.

What are some common challenges faced by ml data associates when labeling complex datasets, and how can they be effectively addressed?

ML Data Associates often encounter challenges with ambiguous data, inconsistent labeling guidelines, or rapidly evolving project requirements. To address these, it's important to maintain open communication with data scientists and project leads, ask clarifying questions, and participate in regular calibration sessions to ensure consistency. Utilizing annotation tools efficiently and staying up-to-date with best practices can also help manage complexity and improve label quality. Collaboration and feedback within the team are key to overcoming these challenges and ensuring high-quality datasets.

What is the difference between Ml Data Associate vs Data Analyst?

AspectML Data AssociateData Analyst
Required CredentialsTypically a degree in computer science, data science, or related field; familiarity with machine learning conceptsUsually a degree in statistics, mathematics, or business analytics; strong Excel and data visualization skills
Work EnvironmentTech companies, AI startups, or organizations focusing on machine learning projectsBusiness, finance, marketing, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing AI models, machine learning pipelines, and data infrastructureCommon across industries for reporting, trend analysis, and strategic decision-making

While both roles involve working with data, ML Data Associates focus on preparing and managing data specifically for machine learning models, whereas Data Analysts interpret data to generate business insights. The roles overlap in data handling skills but differ in their end goals and technical focus.

How do I become an ML Data Associate?

To become an ML Data Associate, candidates typically need a high school diploma or equivalent, along with strong attention to detail and organizational skills. Familiarity with data management tools, basic understanding of machine learning concepts, and experience with data annotation or labeling are often required. Some roles may also require knowledge of programming languages like Python or experience with data annotation platforms.

What skills do you need for a machine learning data associate job?

A machine learning data associate needs strong analytical skills, attention to detail, and proficiency in data management tools like Excel, SQL, or Python. Knowledge of data cleaning, labeling, and basic understanding of machine learning concepts are also important for the role.

What are popular job titles related to Ml Data Associate jobs in Washington?

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What job categories do people searching Ml Data Associate jobs in Washington look for?

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What cities in Washington are hiring for Ml Data Associate jobs?

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Ml Data Associate jobs near you
Infographic showing various Ml Data Associate job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 66% Full Time, 31% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $77,061 per year, or $37 per hour.

Associate AI/ML Data Scientist (Systems Architecture, Associate)

RPMGlobal

Reston, VA • On-site

$150 - $180/hr

Other

Medical, Life, Retirement, PTO

Posted 6 days ago

Job description

Associate AI/ML Data Scientist (Systems Architecture, Associate) Position Location Reston, VA

BA/BS or HS/GED and Equivalent Work Experience

Required

The MIL Corporation is seeking a highly experienced, senior-level Associate AI/ML Data Scientist (Systems Architecture, Associate) to lead the design and implementation of enterprise-scale data platforms to support a federal government customer’s large-scale Agentic AI transformation initiative in Reston, VA.

With extensive experience delivering AI and machine learning solutions in complex enterprise environments, the AI/ML Data Scientist will serve as a technical leader responsible for architecting the data ecosystem that powers vector search, Retrieval-Augmented Generation (RAG), large language model (LLM) applications, and emerging Agentic AI capabilities. This role will work across infrastructure, cybersecurity, software engineering, and mission stakeholders to rapidly deliver scalable, secure, and reliable AI solutions.

This role requires a seasoned engineer capable of communicating complex technical concepts and architectural tradeoffs to senior leaders, helping leadership teams understand the operational, mission, security, and business implications of emerging AI technologies while driving successful implementation of enterprise capabilities.

This position currently requires an on-site schedule. Schedule is subject to change based on company/contract requirements.

Responsibilities

  • Enterprise AI Platform Engineering: Architect, build, and maintain enterprise-scale data platforms supporting vector databases, semantic search, Retrieval-Augmented Generation (RAG), Agentic AI systems, and large language model applications.
  • Data Architecture & Strategy: Establish and implement controls for data quality, lineage, source attribution, prompt and context traceability, explainability, and evaluation of AI system outputs.
  • AI Data Governance: Establish and implement controls for data quality, lineage, source attribution, prompt and context traceability, explainability, and evaluation of AI system outputs.
  • Technical Leadership: Lead architectural decision-making for AI-supporting data infrastructure, balancing performance, scalability, security, reliability, maintainability, and cost considerations.
  • Cross-Functional Integration: Partner with Data Scientists, Machine Learning Engineers, Architects, Cybersecurity teams, and Software Engineers to translate AI requirements into production-grade capabilities.
  • Executive Communication: Translate highly technical AI, machine learning, and data architecture concepts into clear operational impacts, risks, opportunities, and implementation considerations for senior leadership.
  • Enterprise Coordination: Coordinate with stakeholders across multiple organizations to align AI initiatives, maximize reuse of enterprise capabilities, and eliminate duplication of effort.
  • Operational Excellence: Implement monitoring, observability, and alerting to ensure reliability, performance, and continuous improvement of AI-supporting data platforms.
  • Mentorship & Engineering Excellence: Provide technical leadership and mentorship to engineers while promoting engineering best practices and innovation across the organization.
  • Technology Evaluation: Assess emerging AI technologies, vector database platforms, retrieval frameworks, and engineering approaches to improve organizational AI capabilities.

Travel

None

Required Qualifications

  • 8+ years of progressive experience in software engineering, data engineering, distributed systems, cloud architecture, or AI/ML platform development.
  • Proven experience designing and delivering enterprise-scale AI, machine learning, generative AI, or Agentic AI solutions.
  • Demonstrated success architecting and implementing production cloud-native data systems supporting advanced analytics and AI workloads.
  • Proven experience working within complex enterprise environments managing security, infrastructure, technology dependencies, governance requirements, and competing priorities.
  • Extensive experience designing data pipelines supporting machine learning models, vector databases, semantic search capabilities, and generative AI applications.
  • Proven experience delivering complex technical solutions from strategic requirements through operational deployment while balancing schedule, performance, capability, and cost objectives.
  • Technical Expertise:
    • Expert proficiency in Python, SQL, and modern software engineering practices.
    • Deep experience with Azure, AWS, or Google Cloud data and AI platforms.
    • Strong understanding of distributed systems, cloud-native architectures, MLOps, and AI platform engineering.
    • Experience implementing vector databases, embedding pipelines, retrieval systems, and Retrieval-Augmented Generation architectures.
    • Experience with CI/CD pipelines, orchestration platforms, infrastructure automation, and observability tooling.
  • Exceptional written and verbal communication skills.
  • Ability to communicate complex technical concepts to both technical and non-technical audiences.
  • Proven ability to explain AI, machine learning, and data architecture concepts in terms of mission impact, operational outcomes, technical risk, and implementation tradeoffs.
  • Experience influencing decisions and driving consensus among diverse technical and business stakeholders.

Desired Qualifications

  • Experience serving as a Principal Engineer, Lead Data Engineer, Solution Architect, or Technical Lead.
  • Experience building and operating enterprise-scale vector search, RAG, knowledge management, and LLM-based platforms.
  • Hands‑on experience with large‑scale distributed data processing frameworks.
  • Experience leading engineering teams and mentoring junior and mid‑level engineers.
  • Experience supporting AI adoption efforts within large government, defense, intelligence, or highly regulated organizations.
  • Familiarity with AI governance, model evaluation frameworks, explainability, and responsible AI implementation practices.

Education

Bachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related quantitative discipline. Equivalent additional experience may be considered in lieu of degree.

Clearance

All applicants for this position must currentlypossessa Top Secret/SCI with CI Polygraph clearance ; please note that the clearance processtakes into accountfinancial background aspects.

Compensation

The MIL Corporation values your contributions and offers a range of benefits to support your overall well-being. We are pleased to offer a comprehensive range of benefits to our full‑time employees which include health, life, disability, and retirement plans, as well as paid time off, opportunities for professional growth and tuitionassistance.Additionalbenefits and incentives may also apply, which will be communicated during the hiring process.

For this position, the projected compensation range is $150,000 - $180,000per year. This estimaterepresentsthe typical salary range and is just one part of MIL’s complete compensation package. Final salary for this position isdeterminedbased on factors such as individual qualifications, education, experience, and contractual limitations.Learn more on the MIL Careers page.

Why MIL?

The MIL Corporation (MIL) is a dynamic workforce of industry professionals who deliver world‑class solutions in cyber, engineering, financial management, and information technology – and we are looking for candidates like you! MIL offers opportunities for professionals at all stages of their careers, from early‑career candidates to experienced industry professionals. We are known for a collaborative, people‑first culture where employees are supported, valued, and encouraged to grow. This commitment to our people and our work is reflected in the industry and workplace awards MIL has received over the years.

  • 2017 - 2025 Top Workplaces Award, Greater Washington Area (The Washington Post)
  • 2018 - 2025 Certified Great Workplace, Great Place to Work®
    • 2021 - 2025, Best Workplaces in Consulting & Professional Services™
    • 2021 Fortune Best Workplaces for Millennials™
    • 2018 Fortune, Great Place to Work: Best Place to Work for Diversity
  • 2017, 2020 - 2025 Top Workplace Award, South Carolina (Greenville Business Magazine, Columbia Business Monthly, and Charleston Business Magazine)
  • 2025 Corporate Partnership Award, Association of Fundraising Professionals, Maryland Chapter
  • 2024 Patriot Award,Employer Support of the Guard and Reserve (ESGR), Department of Defense
  • 2022 Freedom Award, Employer Support of the Guard and Reserve (ESGR), Department of Defense
  • 2018, Above & Beyond Award, Employer Support of the Guard and Reserve (ESGR), Department of Defense

If your goal is to help the federal government deploy leading technologies, improve financial management, or defend the nation in cyberspace, MIL welcomes you. Become a part of something greater, where you, the people, make the difference.

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by state or federal law.

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