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Machine Learning Testing Jobs in Washington (NOW HIRING)

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.

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.

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.

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.

Machine Learning Engineer II The Machine Learning Engineer II will be a member of the Learning and ... verification testing. This role also involves support for experimentation and fielded systems ...

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 ...

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 ...

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 ...

... 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 ...

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 ...

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 ...

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

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 ...

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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 Jun 19, 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.

Is ML a high paying job?

Machine Learning testing roles are generally well-paid due to the specialized skills required, such as knowledge of algorithms, programming, and data analysis. Salaries vary based on experience, location, and company size, but they tend to be higher than average for tech-related positions.

What jobs pay $2000 a day?

In the field of machine learning testing, highly specialized roles such as senior machine learning engineers, AI research consultants, or freelance experts with advanced skills and certifications can command daily rates of $2000 or more. These positions typically require extensive experience, strong technical knowledge, and often involve consulting or contract work for organizations seeking advanced AI solutions.

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.

How much do AI testers get paid?

AI testers, a role within machine learning testing, typically earn salaries ranging from $60,000 to $120,000 annually depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with skills in programming, data analysis, and testing tools can earn higher wages.

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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms with competitive compensation packages.
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:
Machine Learning Engineer

Other

Posted 19 days ago


Job description

Venture Global LNG ("Venture Global") is a long-term, low-cost provider of American-produced liquefied natural gas. The company's two Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global's modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost.
The Machine Learning Engineer will design, develop, and maintain the productionization of machine learning, deep learning, generative AI, large language models, simulation, and optimization algorithms. This includes building pipelines for training and deploying deep learning and other machine learning algorithms and enabling models to run efficiently in production. The main data engineering work will be done in Databricks and PySpark.
The ideal candidate will have excellent technical proficiency, excellent communication skills, a self-driven mindset, and the willingness to continuously learn new things.
This position will report to the Director of Business Intelligence and is structured within IT under the Vice President of Applications.
The position will be located in Arlington, VA and will require commuting to the office 5 days a week.
Responsibilities
  • Work with business stakeholders to define project requirements.
  • Orchestrate, scale, setup and improve model serving pipelines.
  • Improve model accuracy through feature engineering, tuning, and observability.
  • Improve model computational performance through all aspects of the pipeline, including tuning clusters/job compute, partitioning, caching, feature engineering code, tuning setup, etc.
  • Integrate machine learning models into production environments, ensuring reliability and scalability.
  • Evaluate pretrained models and software from vendors and support integration into production environments.
  • Develop comprehensive project plans for implementing machine learning and AI projects including solution architectures, resourcing, and dependencies.
  • Provide ETL requirements to data engineers to effectively curate files for data analytics.
  • Work with data scientists, data engineers, and business analysts to translate business requirements into machine learning solutions.
  • Build software solutions that are maintainable, scalable and provide quantifiable business value.
  • Continuously focus on quality architecture, quality code, and ruthless management of technical debt.
  • Continuously push the practice forward, learning and testing newer and better ways of performing work.

Required Qualifications
  • 5 years of machine learning engineering, software engineering, or data science experience.
  • Bachelors in a quantitative field of study.

Preferred Qualifications
  • Masters in a quantitative field of study.
  • Experience with the Azure, AWS, or other cloud ecosystems.
  • Experience in building secure data processing pipelines.
  • Proficient in utilizing data lakes, CI/CD pipelines, Databricks, Unity Catalog, and Git.
  • Experience working with streaming.
  • Expertise in building machine learning solutions using cloud data services.
  • Exceptional skills in data processing languages such as SQL, Python, or Scala.
  • Exceptional skills in feature engineering, model optimization, and parameter tuning.

Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.
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