Principal Scientist - AI / ML

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 300+ 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 Principal Scientist. As a Principal Scientist, you will have the opportunity to lead and shape the technical direction of our AIML research initiatives, mentor junior researchers, and drive the development of state-of-the-art prognostics, diagnostic, and modeling solutions.

Job Description

Roles and responsibilities

• Provide technical leadership and vision for the development of advanced algorithms and methodologies in artificial intelligence and machine learning (AIML) to drive process and product innovation.
• Develop and implement research strategies to identify and prioritize areas of focus for AIML research, ensuring alignment with business objectives and industry trends.
• Mentor and guide junior researchers, including Senior Engineers and Scientists, to help them develop their technical skills and expertise in AIML, and provide guidance on project leadership and management.
• Drive innovation in AIML by staying at the forefront of advancements in the field, through literature reviews, active participation in conferences and seminars, and collaboration with external research institutions and industry partners.
• Lead large-scale research projects, including project planning, resource allocation, and team management, to ensure successful project execution and delivery of high-impact results.
• Collaborate with cross-functional teams, including engineers, researchers, and product managers, to seamlessly integrate AIML solutions into existing system platforms and drive business impact.
• Drive intellectual property development by authoring invention disclosures, filing patents, and publishing research in high-impact scientific journals and presenting findings at leading conferences.
• Identify and develop talent within the organization, including recruiting and hiring new researchers, and providing training and development opportunities to help them grow in their careers. This will include partnering with the Advanced Research Center (ARC) leadership to develop and implement talent development strategies, and collaborating with the ARC team to identify and develop future research leaders.
• Maintain and expand technical expertise in machine learning, artificial intelligence, and related fields, including proficiency in programming languages and frameworks commonly used in AIML applications, such as Python, TensorFlow, PyTorch, and others.
• Communicate complex technical concepts and research findings to both technical and non-technical audiences, including business leaders, customers, and external partners.
• Develop and implement strategies to drive the adoption of AIML solutions within the organization, including working with business leaders to identify opportunities for AIML to drive business impact.
• Develop and propose innovative ideas for AIML research projects, and secure funding for these projects through internal sources, such as the GE Vernova research funding program, and external sources, such as industry partnerships and collaborations.
• Manage project budgets and resources, and ensure that projects are delivered on time, within budget, and to the required quality standards.

Required Qualifications

Preferred Qualifications

Additional Information

Relocation Assistance Provided : Yes

Skills Required

Tensorflow, Numpy, Git, Machine Learning, Pandas, Pytorch, Docker, Artificial Intelligence, Agile Methodologies, Python