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Intern

GE Vernova · Posted Oct 15

Power generation, wind turbine, grid solution, and electrification services

EPIP 122 (Phase II), Whitefield Road, Bengaluru, Karnātaka, 560066, IndiaInternshipOnsiteIntern/New Grad₹4.8L–₹9.0L yearly100+ applicants
EnergyPower GenerationRenewable EnergyElectrificationWind EnergyPublic Company
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About the role

GE Vernova's Advanced Research business is the central innovation engine for GE's portfolio of energy businesses, with 400+ researchers driving programs to decarbonize power, accelerate renewables, electrify, and build a 21st century grid. The internship is in the field of Artificial Intelligence, focused on machine learning theory and applications including time series analysis, machine vision, and deep learning. The intern will design research experiments, develop and implement novel AI/ML algorithms, evaluate models on time series and visual data, and document findings in technical reports and presentations.

What you will do

  • Assist in designing and developing research experiments to address key challenges in time series analysis, machine vision, and deep learning applications.
  • Develop novel AI/ML algorithms and implement them in Python, PyTorch, TensorFlow, or similar environments.
  • Build and evaluate machine learning and deep learning models for the analysis of time series data and visual data; conduct experiments to validate algorithm performance across various datasets and scenarios.
  • Analyze experimental results to validate theoretical assumptions, assess model accuracy, and derive actionable insights for further refinement.
  • Conduct comprehensive literature reviews to stay abreast of state-of-the-art techniques in time series forecasting, computer vision, and deep learning architectures.
  • Document research methodologies, experimental setup, results, and findings in technical reports, papers, and presentations for both internal and external dissemination.

Skills used in this role

PythonPyTorchTensorFlowKerasNumPypandasmatplotlibOpenCVmachine learningdeep learningcomputer visiontime series analysisdata visualizationfeature engineeringproblem solvingcommunication

What the employer is looking for

  • Currently enrolled in a Master’s or Ph.D. program in Computer Science, Electrical/Electronics Engineering, Applied Mathematics, Data Science, or a related field, with a focus on AI, Machine Learning, or Data Analytics.
  • Experience developing in Python and familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or Keras.
  • Proficiency in building and evaluating statistical, machine learning, and deep learning models for time series and/or image data.
  • Experience with data processing, feature engineering, and data visualization tools and libraries (e.g., NumPy, pandas, matplotlib, OpenCV).
  • Excellent analytical and problem-solving skills, with the ability to critically evaluate research findings and propose innovative solutions.
  • Strong communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment.

Benefits and support

  • Relocation Assistance Provided

About GE Vernova

GE Vernova Inc. is a global energy company that provides equipment, services, and software to generate, transfer, orchestrate, convert, and store electricity. Operating through its Power, Wind, and Electrification segments, the company supports a broad customer base across more than 100 countries in powering economies and driving the energy transition. Formed as part of the strategic spin-off of General Electric's energy portfolio, GE Vernova is dedicated to electrifying and decarbonizing the world.

Industry
Energy
Company size
75000+ employees
Founded
2024
Location
Cambridge, Massachusetts, USA
Funding stage
Public Company

Leadership

SS
Scott Strazik

Chief Executive Officer and President

SF

Stephen F. Angel

Chairman of the Board

LL

Lola Lin

Chief Legal Officer and Secretary

RM

Roger Martella

Chief Corporate Officer, Chief Sustainability Officer & Head of Global Government Affairs

EG

Eric Gray

CEO, Power Segment