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Machine Learning Testing Jobs in Washington (NOW HIRING)

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Design evaluation pipelines, metrics, and testing frameworks to measure model capabilities ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Design evaluation pipelines, metrics, and testing frameworks to measure model capabilities ...

AISquared

Machine Learning Engineer

Washington, DC · On-site

... Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ... workflows, integrating testing, validation, and automated deployment. • Optimize runtime ...

Kitware

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment * Machine learning experience ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment * Machine learning experience ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment * Machine learning experience ...

Xometry

Senior Machine Learning Engineer

North Bethesda, MD · Hybrid

$104K - $143K/yr

Xometry is seeking a Senior Machine Learning Engineer to join our growing organization. The right ... Strong software fundamentals with experience in design patterns, refactoring, OOP, and testing * A ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

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

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

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

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

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

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

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

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Machine Learning Testing information

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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.
Machine Learning Engineer

Machine Learning Engineer

AI Squared

Washington, DC • On-site

Full-time

Re-posted 19 days ago

Job description

Machine Learning Engineer
Washington, DC (Hybrid)

About the Role:

We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You'll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.

Key Responsibilities:
  • Design, implement, and maintain ML deployment pipelines for scalable production systems.
  • Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
  • Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
  • Partner with data scientists to transition models from research/prototype into production-ready deployments.
  • Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
  • Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
  • Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
  • Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.
Qualifications:
  • 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
  • Proven experience deploying and maintaining machine learning models in production at scale.
  • Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
  • Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
  • Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
  • Strong understanding of MLOps best practices, monitoring, and automation.
  • Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
  • Strong communication and collaboration skills across technical and non-technical teams.