Lead Research Engineer - AI/ML

India·Bangalorelead

OtherResearch Engineer

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Quick Summary

Key Responsibilities

Lead the development of advanced algorithms and methodologies in artificial intelligence and machine learning (AIML) to drive process and product innovation.

Requirements Summary

PhD with 3-7 years relevant experience or Masters with 6 -10 years relevant experience from a reputed institution. Extensive understanding and experience in machine learning, artificial intelligence,

Technical Tools

OtherResearch Engineer

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 lead researcher to join our team in the field of Artificial Intelligence, Machine Learning (AIML). As a Lead 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.

Responsibilities

~2 min read

→Lead the development of advanced algorithms and methodologies in artificial intelligence and machine learning (AIML) to drive process and product innovation.
→Oversee the analysis of extensive datasets to identify complex patterns, trends, and insights, with an emphasis on diagnostics and prognostics for large-scale energy equipment.
→Architect and optimize AIML algorithms and models to ensure superior performance and scalability.
→Design, conduct, and supervise experiments to assess the efficacy and reliability of AIML-based solutions.
→Document and disseminate research findings, methodologies, and implementation strategies for effective knowledge sharing and future reference.
→Collaborate with and guide cross-functional teams, including engineers, researchers, and product managers, to seamlessly integrate AIML solutions into existing system platforms.
→Stay at the forefront of advancements in AIML, control systems, and signal processing engineering, through literature reviews, and active participation in conferences and seminars.
→Lead research initiatives to conceptualize and develop AI solutions for complex industrial challenges.
→Mentor junior researchers and contribute to project leadership, ensuring alignment with strategic objectives.
→Demonstrate the impact of AI through advanced prototypes and solutions that address real-world problems.
→Utilize and advocate for best practices in software libraries, tools, and methodologies to implement efficient, scalable, and reusable solutions.
→Drive intellectual property development by authoring invention disclosures and filing patents.
→Publish research in high-impact scientific journals and present findings at leading conferences.

Required Qualifications:

→PhD with 3-7 years relevant experience or Masters with 6 -10 years relevant experience from a reputed institution.
→Extensive understanding and experience in machine learning, artificial intelligence, and related fields.
→Proven track record of applying multiple advanced AIML concepts to practical applications.
→Proficiency in programming languages and frameworks commonly used in AIML applications, such as Python, TensorFlow, PyTorch, and others.
→Expertise in data analysis and manipulation using tools like pandas, NumPy, and proficiency in software development best practices, including version control (e.g., Git) and agile methodologies.
→Strong leadership capabilities, excellent problem-solving skills, and ability to think critically and creatively.
→Superior communication skills and ability to lead, mentor, and work effectively in a collaborative team environment.
→Demonstrated ability to build advanced prototypes and rapidly develop proof-of-concepts to illustrate solution feasibility.