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Director Google Machine Learning Engineer Jobs in Virginia

Samprasoft

Machine Learning Engineer

Mclean, VA · On-site

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

ICONMA

Machine Learning Engineer

Mclean, VA · On-site

Machine Learning Engineer Our client, a financial company, is looking for a Machine Learning Engineer for their McLean, VA location. Requirements: * Python, AWS, Kubernetes, Kubeflow, MLOps, ML ...

WorkNovas LLC

Machine Learning Engineer

Richmond, VA · On-site

Machine Learning Engineer Richmond, Virginia (5 Days Onsite) need local within commute About the ... Direct experience with Azure AI Foundry and Copilot Studio Experience integrating AI agents into ...

Capital One

Senior Machine Learning Engineer

Richmond, VA · On-site +1

$103.40K - $142K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

1872 Consulting

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer D.C. Area About the Position As a member of our Engineering team, you will work with a tight, highly skilled machine learning / data science team dedicated to the ...

NT Concepts

Machine Learning Engineer

Vienna, VA · On-site +1

Machine Learning Engineer Chantilly, VA We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you are part of an innovative, agile company dedicated to ...

Capital One

Senior Machine Learning Engineer

Mclean, VA · On-site

$105.60K - $145.10K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

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Infographic showing various Director Google Machine Learning Engineer job openings in Virginia as of May 2026, with employment types broken down into 78% Full Time, 12% Part Time, and 10% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Venture Global LNG

Arlington, VA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Machine Learning Engineer

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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