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Temporary Machine Learning Testing Jobs (NOW HIRING)

A/B Testing and Experimentation : Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance ...

$150 - $200/hr

Strong experience designing, building, training, and testing machine learning models end‑to‑end. * Proven ability to work with raw, unstructured, or incomplete data, including data collection ...

Machine Learning Engineer

Bellevue, WA · On-site

$150 - $200/hr

A/B Testing and Experimentation : Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance ...

Machine Learning Engineer

Bellevue, WA · On-site

$150 - $200/hr

A/B Testing and Experimentation : Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance ...

A/B Testing and Experimentation : Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Strong experience designing, building, training, and testing machine learning models end-to-end. * Proven ability to work with raw, unstructured, or incomplete data, including data collection ...

A background in machine learning, hypothesis testing, regression analysis, statistics, text analytics, and predictive analytics with noisy data is necessary. Technical Skills: Candidates must have ...

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

Chatsworth, CA · On-site

$160K - $190K/yr

Strong experience designing, building, training, and testing machine learning models end-to-end. * Proven ability to work with raw, unstructured, or incomplete data, including data collection ...

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.

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Temporary Machine Learning Testing information

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How much do temporary machine learning testing jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for temporary machine learning testing in the United States is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $25.48 per hour, depending on experience, location, and employer.

What is the difference between Temporary Machine Learning Testing vs Data Scientist?

AspectTemporary Machine Learning TestingData Scientist
CredentialsTypically requires knowledge of machine learning tools, programming, and basic statisticsRequires advanced degrees (e.g., Master’s or PhD) in data science, statistics, or related fields
Work EnvironmentProject-based, often temporary roles focused on testing models and algorithmsLong-term, strategic roles involving data analysis, model development, and business insights
Industry UsageCommon in tech, finance, and research sectors for specific testing tasksWidely used across industries for data-driven decision making

Temporary Machine Learning Testing roles focus on evaluating and validating machine learning models in short-term projects, while Data Scientists develop, implement, and interpret complex data models for ongoing business strategies. Both roles require technical skills, but Data Scientists typically have higher educational credentials and broader responsibilities.

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Infographic showing various Temporary Machine Learning Testing job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $47,468 per year, or $22.8 per hour.

Engineer, Machine Learning

Arlington, VA

$157K - $185K/yr

Full-time

Re-posted 2 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 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.

We are seeking qualified applicants for the position:

Engineer, Machine Learning

Located:

Arlington

Summary

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.

General Description Duties & 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.

Qualifications

Required experience

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

Preferred Experience

  • 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.

Salary Range

$157,000-$185,000

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.