Research Scientist - Machine Learning

Job Description Summary

GE Vernova's Advanced Research business is the central innovation engine for GE's portfolio of energy businesses, which is unified under one banner called GE Vernova. The research organization is made up of 250+ researchers representing virtually every major scientific and engineering discipline. Collectively, they are driving major research programs and initiatives to decarbonize power, accelerate renewables, and promote electrification and the creation of a 21st century grid fit to power a zero-carbon energy future.

We are seeking a highly motivated and skilled researcher to join our team in the field of Artificial Intelligence, Machine Learning (AIML). As a Research Engineer, you will have the opportunity to work closely with our experienced engineers and researchers on cutting-edge projects that leverage AIML techniques for the development of state-of-the-art prognostics, diagnostic and modelling solutions.

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• Develop novel AIML algorithms and methodologies applicable to control systems engineering and anomaly detection problems.
• Analyse large time series datasets to identify patterns, trends, and insights to deliver algorithms dealing with diagnostics and prognostics of large energy equipment.
• Implement and optimize AIML algorithms and models.
• Design and conduct experiments to test the performance and robustness of AIML-based solutions.
• Document research findings, methodologies, and implementation details for knowledge sharing and future reference.
• Collaborate with cross-functional teams, including engineers, researchers, and product managers, to integrate AIML solutions into existing system platforms.
• Keep abreast of the latest advancements in AIML, control systems, and signal processing engineering through literature review and participation in relevant conferences and seminars.

• PhD with 2 - 5 Years Experience or Master's degree with 5 - 7 Years Experience from a reputed institution in Computer Science or other engineering field.
• Strong understanding of fundamental concepts in statistics, machine learning, and artificial intelligence.
• Proficiency in programming languages commonly used in AIML applications such as Python, PySpark, PyTorch, Pandas, or similar.
• Experience with data analysis and manipulation using tools like Pandas, NumPy, or MATLAB. Familiarity with software development best practices, including version control (e.g., Git) and agile methodologies.
• Basic knowledge of cloud-based architectures
• Excellent problem-solving skills and ability to think critically and creatively.
• Strong communication skills and ability to work effectively in a collaborative team environment.
• Demonstrated ability to build prototypes and quickly develop proof of concepts to show solution feasibility.