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Machine Learning Testing Jobs in Washington (NOW HIRING)

Capital One

Sr Lead Machine Learning Engineer

Mclean, VA · On-site

Sr Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Solve complex problems by writing and testing application code, developing and validating ML models ...

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Machine Learning Testing information

See Washington salary details

$15

$25

$35

How much do machine learning testing jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for machine learning testing in Washington is $25.85, according to ZipRecruiter salary data. Most workers in this role earn between $22.31 and $28.85 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Testing position, and why are they important?

To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.

What are the typical challenges faced by professionals in Machine Learning Testing roles?

Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.

What is a Machine Learning Testing job?

A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.

What are popular job titles related to Machine Learning Testing jobs in Washington? For Machine Learning Testing jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Machine Learning Testing jobs in Washington look for? The top searched job categories for Machine Learning Testing jobs in Washington are:
Machine Learning Testing jobs near you
Infographic showing various Machine Learning Testing job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $53,762 per year, or $25.8 per hour.
AI Machine Learning Engineer

AI Machine Learning Engineer

Niyam IT, Inc.

Ashburn, VA • On-site, Remote

Full-time

Re-posted 9 days ago

Job description

About Niyam IT (Niyam)

Niyam was founded in 2007 by a group of consultants who shared a unique vision: a technology company steeped in orderly process yet driven by passion and innovation. Over the following decade, we fine-tuned our craft and built an impressive track record of successful outcomes, securing our reputation as the go-to provider of smart, innovative solutions.


Today, Niyam is at the forefront of the industry, leading the way in crafting mission-critical technologies for Emergency Preparedness & Response, Natural Resource Management, Law Enforcement & Justice, Health IT, and Global Citizen Services.


What We Offer:

  • Flexible Work Hours: Life doesn't always fit into a 9-to-5 schedule. We offer flexibility to help you manage your work-life balance effectively.
  • Remote Work: Niyam understands the value of flexibility. We offer remote work.
  • Career Growth: Niyam is not just a job; it's a career journey. We provide a supportive environment for your professional development and offer fully paid opportunities for training and advancement within the company.
  • Great People: Our people are the blueprint of who Niyam is to the industry and community.
  • Great Environment: Niyam fosters a great environment where innovation, collaboration, and personal growth thrive.
  • Diversity & Inclusion: We believe in the strength of diverse perspectives. Your unique ideas are welcomed and celebrated every day at Niyam.


Join us in creating a workplace where innovation, diversity, and well-being thrive. Your journey at Niyam awaits. Apply today!


Niyam is seeking an AI/ML Engineer to join our team in support of our work with a federal client. This role will focus on designing, developing, and deploying advanced AI/ML solutions that enhance operational efficiency, enable data-driven decision-making, and support evolving mission needs.The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps, along with experience working in secure, regulated environments. This position requires collaboration across cross-functional teams and a commitment to delivering scalable, ethical, and compliant AI solutions.We offer competitive compensation and benefits. This full-time position will be hybrid to Ashburn, VA. This position is contingent upon award of contract.


Roles and Responsibilities

    • Design, develop, train, and validate advanced AI and machine learning models to support mission-critical use cases for a federal client, ensuring alignment with operational objectives and data governance standards.
    • Evaluate and select appropriate machine learning techniques, algorithms, and neural network architectures (e.g., supervised, unsupervised, deep learning), leveraging frameworks such as TensorFlow and PyTorch to build scalable and efficient solutions.
    • Perform end-to-end data lifecycle activities, including data collection, ingestion, cleansing, preprocessing, and feature engineering, ensuring data quality, integrity, and compliance with federal data management policies.
    • Deploy AI/ML models into production environments, integrating with existing enterprise systems, cloud platforms, and APIs while ensuring high availability, scalability, and security.
    • Establish and maintain MLOps pipelines to support continuous integration, continuous delivery (CI/CD), automated testing, model versioning, and performance monitoring across the model lifecycle.
    • Monitor model performance over time, implement retraining strategies, and optimize models to ensure sustained accuracy, reliability, and operational effectiveness in dynamic environments.
    • Identify, assess, and mitigate bias in datasets and model outputs, ensuring fairness, transparency, and adherence to ethical AI principles and applicable federal guidelines.
    • Collaborate with cross-functional teams, including data engineers, software developers, cybersecurity personnel, and program stakeholders, to translate mission and business requirements into technical AI/ML solutions.
    • Document model development processes, methodologies, and results to support auditability, reproducibility, and compliance with federal standards and accreditation requirements.
    • Support security and compliance initiatives by aligning AI/ML solutions with frameworks such as NIST and FedRAMP, ensuring proper handling of sensitive data and adherence to system authorization processes (e.g., ATO).


    Qualifications and Education Requirements:

    • US Citizenship with ability to obtain a Public Trust.
    • Bachelor's degree or higher in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related technical discipline from an accredited institution.
    • 8+ years of progressive experience designing, developing, and deploying machine learning or artificial intelligence solutions within enterprise or mission-driven environments.
    • Demonstrated experience with machine learning frameworks and tools such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.
    • Hands-on experience with data preprocessing, feature engineering, and working with large, complex datasets in both structured and unstructured formats.
    • Proven experience deploying and operationalizing AI/ML models in production environments, including integration with cloud platforms (e.g., AWS, Azure, or GCP).
    • Experience implementing MLOps practices, including CI/CD pipelines, model monitoring, versioning, and lifecycle management.
    • Strong understanding of responsible AI practices, including bias detection, model explainability, and ethical AI considerations.
    • Familiarity with federal security and compliance frameworks (e.g., NIST, FedRAMP) and experience working within regulated environments is preferred.
    • Strong analytical, problem-solving, and communication skills, with the ability to effectively collaborate across technical and non-technical stakeholders.
    • Local to Ashburn, VA and available to work onsite as needed.


    Preferred Skills:

    • Experience supporting federal agencies or working within government contracting environments.
    • Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).
    • Experience with big data technologies such as Hadoop, Spark, or distributed data processing frameworks.
    • Familiarity with API development and microservices architecture.
    • Experience implementing AI/ML solutions in cloud-native environments.

    Application Deadline:This position will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.


    Niyam is an Equal Opportunity ("EEO") Employer. All qualified applicants will receive consideration without regard to race, color, creed, religion, sex, sexual orientation, gender identity, pregnancy, marital status, partnership status, age, citizenship status, veteran or military status, medical condition, genetic information, national origin, disability, unemployment status or any other characteristic prohibited by federal, state and/or local laws.If you require a reasonable accommodation due to a disability to complete your application, or if you face challenges using our online application system and need an alternative way to apply, please reach out to us at +1 703.429.2450 or email hr@niyamit.com.

    Apply