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Machine learning Jobs in Alexandria, VA
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Machine learning • alexandria va
Machine Learning Engineer
Venture Global LNGArlington, VAMachine Learning Engineer
Booz Allen HamiltonWashington, D.C.Machine Learning Engineer
eTeam IncWashington, District of Columbia, United States- Promoted
Senior Data Scientist - Python & Machine Learning
Castellum IncWashington, District Of Columbia, United StatesRemote Machine Learning Engineer Talent Network - AI Trainer ($70-$250 per hour)
MercorWashington, District of Columbia, USSenior Manager, Learning & Development
CAVA - Support CenterDistrict of Columbia, District of Columbia, United StatesExtended Learning, Support Teacher
Achievement Prep Public Charter SchoolsWashington, DC, DC, USDish Machine Operator
IHOPWashington, DC, US- Promoted
Machine Tool Trainee
TradeJobsWorkforce22214 Arlington, VA, US- Promoted
Transfer Machine Operator
Longhorn Energy and Transportation LLCClinton, MD, United States- Promoted
Learning & Business Partner Specialist
Howard University HospitalWashington, DC, United StatesData Science/Machine Learning Engineer (Remote, Continental United States)
ICA.aiArlington, Virginia, United StatesVice President, Jewish Learning
Leading EdgeDC, United StatesMachine Learning Engineer - Autonomy Lab
Carnegie Mellon UniversityArlington, VA- Promoted
Learning Specialist
InsideHigherEdWashington D.C., United States- Promoted
Transfer Machine Operator
amrizeClinton, MD, United StatesSenior Front-end Engineer, WWPS ProServe Data and Machine Learning
Amazon Web Services, Inc.Arlington, Virginia, USASr. Learning Experience Designer (LXD), Workforce Staffing Learning & Development
Amazon.com Services LLCArlington, Virginia, USAAssociate Director, Online Learning
Sparks GroupWashington, DCThe average salary range is between $ 119,550 and $ 175,279 year , with the average salary hovering around $ 125,825 year .
- lead software engineer (from $ 139,375 to $ 245,700 year)
- database engineer (from $ 124,197 to $ 245,700 year)
- senior database administrator (from $ 118,500 to $ 245,700 year)
- psychiatrist (from $ 200,000 to $ 242,500 year)
- oracle database administrator (from $ 195,750 to $ 236,925 year)
- business operations manager (from $ 70,000 to $ 234,900 year)
- inspection (from $ 65,000 to $ 234,900 year)
- associate dentist (from $ 25,000 to $ 230,000 year)
- software engineering manager (from $ 195,000 to $ 226,156 year)
- emergency medicine physician assistant (from $ 200,000 to $ 225,000 year)
- Grand Rapids, MI (from $ 177,531 to $ 240,706 year)
- Lansing, MI (from $ 109,700 to $ 240,100 year)
- Simi Valley, CA (from $ 136,688 to $ 235,450 year)
- Spokane Valley, WA (from $ 135,458 to $ 234,943 year)
- Charleston, SC (from $ 112,230 to $ 233,350 year)
- Chula Vista, CA (from $ 174,990 to $ 229,500 year)
- Fairfield, CA (from $ 151,875 to $ 227,500 year)
- Sunnyvale, CA (from $ 150,000 to $ 225,000 year)
- Hampton, VA (from $ 107,500 to $ 225,000 year)
- Wichita Falls, TX (from $ 145,250 to $ 223,751 year)
The average salary range is between $ 115,000 and $ 195,008 year , with the average salary hovering around $ 146,288 year .
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Machine Learning Engineer
Venture Global LNGArlington, VA- Full-time
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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