GE Vernova - Machine Learning Software Intern - Summer 2027

GE VernovaGE VernovaBellevue, Washington, United States
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Posted

9/28/2026

Employment

Full time, Internship

Range

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Work style

On-site

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AI summary

Core responsibilities

The intern will contribute to the design, implementation, and validation of machine learning algorithms to improve plant efficiency and operational software relevance. They will collaborate with domain experts to validate patterns and integrate solutions into existing equipment monitoring platforms.

Requirements overview

Candidates must be enrolled in a Bachelor's, Master's, or PhD program in Computer Science, Data Science, Computer Engineering, or a related field. Applicants should possess foundational knowledge in machine learning techniques and experience with Python and relevant ML libraries.

Key skills

Machine LearningPythonScikit-learnTensorFlowPyTorchData ScienceTime-series analysisTemporal pattern recognitionAnomaly detectionClustering algorithmsStatistical analysisJupyterGitSoftware developmentPredictive analyticsPrescriptive analytics

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Education requirements

bachelor degreepostgraduate degree

About GE Vernova

Industry

Energy Technology

Employees

70,995

Type

Public Company

Size

10,001+ employees

GE Vernova is a purpose-built energy technology company on a mission to electrify to thrive and decarbonize the world. It is made up of three businesses -- Power, Electrification, and Wind -- with focus on accelerating the path to more reliable, affordable, and sustainable energy, while helping our customers power economies and deliver the electricity that is vital to health, safety, security, and improved quality of life. The world needs more energy, smarter energy. With energy demand expected to grow by more than 50% in the next 20 years, we are continuously innovating to meet the moment…like we have for the past 130 years. The Energy of Change and relentless optimism are what drive us – it’s about never giving up and seeing what’s possible so that we deliver the energy technologies the world needs right now and for generations to come. GE Vernova’s attitude and edge is embedded in its name. We retain our treasured legacy, “GE,” as an enduring and hard-earned badge of quality and ingenuity. “Ver” / “verde” signal Earth’s verdant and lush ecosystems. “Nova,” from the Latin “novus,” nods to a new, innovative era of lower carbon energy that GE Vernova will help deliver. Together, we have the energy to change the world.

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Job categories

SoftwareData & AnalyticsEnergyEngineeringTechnology

Description

Job Description Summary Addressing the climate crisis is an urgent global priority, and at GE Vernova, we take our responsibility seriously. That is the singular mission of GE Vernova: to continue electrifying the world while simultaneously working to help decarbonize it. Innovation Are you passionate about innovation? Are you excited at the opportunity to electrify and decarbonize the world? We operate with a founder’s mindset. We deliver innovation with passion, speed, and courage. We continuously challenge our thinking and are empowered to dream big and take smart risks. What impact you’ll make As a student of the advanced analytics team, Software and Controls Solutions, you will be an active contributor to improving energy companies’ plant efficiency and operation through predictive and prescriptive analytics. Job Description What you’ll do (Job Responsibilities) Contribute to the design, implementation, and validation of algorithms that improve software alert relevance and operational efficiency. Collaborate with domain experts to validate detected patterns and ensure alignment with operational realities. Integrate algorithmic solutions with existing equipment monitoring platforms, ensuring scalability and robustness. Participate in the evaluation of algorithm performance using documented metrics such as false alarm reduction rates and pattern detection accuracy. Document all work clearly in accordance with project standards for reproducibility and knowledge sharing. What you’ll bring (Basic Qualifications) Enrollment in a Bachelors, Masters, or PhD program in Computer Science, Data Science, Computer Engineering, or related field. Foundational knowledge in temporal pattern recognition, time-series analysis, or related ML techniques Experience with Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch). Ability to interpret technical documentation and contribute to collaborative software development projects. What will make you stand out (Desired Qualifications) Prior experience with industrial sensor data, anomaly detection, or event classification. Familiarity with statistical analysis and clustering algorithms. Familiarity with Jupyter and cloud-based environments. Knowledge of version control systems (Git) and collaborative project tools (Confluence, Jira). Additional Information GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Relocation Assistance Provided: No For candidates applying to a U.S. based position only: This posting is expected to remain open for at least seven days after it was posted on September 28, 2026. U.S. Internship roles are ineligible for GE Vernova benefits.

Requirements

  • •Machine Learning
  • •Python
  • •Scikit-learn
  • •TensorFlow
  • •PyTorch
  • •Data Science
  • •Time-series analysis
  • •Temporal pattern recognition
  • •Anomaly detection
  • •Clustering algorithms
  • •Statistical analysis
  • •Jupyter
  • •Git
  • •Software development
  • •Predictive analytics
  • •Prescriptive analytics

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