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Machine Learning Engineer Energy Jobs (NOW HIRING)

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Gotion, Inc.

Machine Learning Engineer

Manteno, IL · On-site

About The Team The Product Development Team at Gotion Illinois New Energy Inc. focuses on the ... Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

About The Team The Product Development Team at Gotion Illinois New Energy Inc. focuses on the ... Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ...

Compunnel

Machine Learning Engineer

Plano, TX · On-site

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Alignerr

Machine Learning Engineer

Richmond, VA · Remote

$50 - $70/hr

Machine Learning Engineer - AI Data Trainer Location: Remote About The Job At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting‐edge AI models.

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NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Spotify

Machine Learning Engineer

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Spotify

Machine Learning Engineer

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

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All JobsMachine Learning Engineer Energy Jobs

Machine Learning Engineer Energy information

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$31.5K

$128.8K

$193.5K

How much do machine learning engineer energy jobs pay per year?

As of Jun 5, 2026, the average yearly pay for machine learning engineer energy in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer in the energy sector, and why are they important?

To thrive as a Machine Learning Engineer in the energy sector, you need strong programming skills (Python, R), a solid background in mathematics and statistics, and typically a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), data analytics platforms, and industry-specific tools like SCADA systems is often required. Excellent problem-solving, collaboration, and communication skills help you translate complex data insights into actionable solutions for energy operations. These competencies enable you to develop effective models that optimize energy systems, drive innovation, and support critical decision-making in a highly technical industry.

What does a Machine Learning Engineer do in the energy sector?

A Machine Learning Engineer in the energy sector develops and deploys algorithms to analyze large datasets, optimize energy systems, and improve efficiency. They may work on predictive maintenance for equipment, demand forecasting, energy consumption analysis, and integrating renewable sources. Their work helps energy companies make data-driven decisions, reduce costs, and support sustainability goals by leveraging advanced machine learning techniques.

What is the difference between Machine Learning Engineer Energy vs Data Scientist?

AspectMachine Learning Engineer EnergyData Scientist
CredentialsBachelor's/Master's in CS, Data Science, or related; experience with ML frameworksBachelor's/Master's in Statistics, Math, or CS; strong analytical skills
Work EnvironmentEnergy sector projects, renewable energy, utilitiesVarious industries including finance, healthcare, tech
Employer & Industry UsageEnergy companies, utilities, renewable firmsBroad industry application across sectors
Search & Comparison IntentFocus on ML applications in energy sectorBroader data analysis and modeling roles

While both roles require strong analytical skills and experience with data tools, Machine Learning Engineers Energy focus on developing and deploying ML models specifically for energy-related applications, whereas Data Scientists analyze data across various industries to generate insights. The roles overlap in skills but differ in industry focus and project scope.

What are some unique challenges Machine Learning Engineers face in the energy sector, and how can they prepare to address them?

Machine Learning Engineers in the energy sector often encounter challenges related to working with large, complex, and sometimes incomplete datasets from sources like smart grids, sensors, or renewable energy systems. Additionally, they must ensure that models are robust enough to handle real-time data and changing operational conditions. Collaborating closely with domain experts, such as energy analysts and engineers, is crucial for understanding the nuances of the data and ensuring that solutions are practical and compliant with industry regulations. Gaining familiarity with industry-specific software and data protocols, as well as developing strong communication skills, can help candidates excel in this role.
Machine Learning Engineer

Machine Learning Engineer

Venture Global LNG

Arlington, VA

Other

Posted 5 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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