Lead Engineer - Machine Learning

Job Description SummaryWe are looking for top notch researchers to be part of our growing Software Controls and Optimization team at GE Aerospace Research. As a group, we innovate and execute on the R&D strategy for GE Aerospace on a range of problems from building predictive/prescriptive analytics for a variety of applications that improve process efficiencies in the business, engine faults to designing inspections solutions for aircraft enginesJob Description

Company Overview

Working at GE Aerospace means you are bringing your unique perspective, innovative spirit, drive, and curiosity to a collaborative and diverse team working to advance aerospace for future generations. If you have ideas, we will listen. Join us and see your ideas take flight!

Site Overview

Established in 2000, the John F. Welch Technology Center (JFWTC) in Bengaluru is our multidisciplinary research and engineering center. Engineers and scientists at JFWTC have contributed to hundreds of aviation patents, pioneering breakthroughs in engine technologies, advanced materials, and additive manufacturing.

Role Overview:

As a Lead Research Engineer Machine Learning, you will:

• Work independently as well as with a diverse team to develop and apply advanced technology solutions to GE Aerospace products and services using modeling, optimization, estimation, or detection technologies, leveraging AI/ML to augment a physics-based understanding of systems.
• Validate performance of developed solution through simulations and application on target product to mature technology to be transferred to the GEbusiness.
• Document technology and results through patent applications, technical reports, andpublications.
• Stay current with advances in system technologies to seek out new ideas andapplications.
• Work in a team environment with colleagues across GE Aerospace Research, and business units.

Ideal candidate:

Should have experience in machine learning

Required Qualifications

• Doctorate degree in an Engineering field with a minimum of 3 years of experience in design of estimation, controls, AI/ML, or fault detection algorithms. Or a Masters degree in an Engineering field with a minimum of 7 years of experience in AI/ML, physics-based modeling, estimation, or fault detection algorithms.
• Knowledge and application of data analytics, optimization, estimation, or detectionalgorithms.
• Proficiency in Python or Matlab and familiarity with C & C++.
• Demonstrated experience (algorithm development and software implementation) in developing systems solutions for complex physical systems (e.g. mechanical systems, aviation systems, power systems, etc.).
• Demonstrated ability to lead teams and execute on large projects.

Desired Qualifications

• Experience with end-to-end development of digital products with exposure to problems in the aero/thermal domain.
• Strong analytical skills, familiarity with robust modeling/analysis techniques.
• Proficiency with use of NPSS for aerospace applications.
• Strong interpersonal skills.
• Self-motivated and ability to work independently and as part of a team.
• Experience leading teams which includes setting up schedules, milestones, technical reviews, tracking funding etc.
• Ability to communicate effectively with senior leadership.
• Demonstrated ability to take an innovative idea from a concept to a product.

• Humble: respectful, receptive, agile, eager to learn
• Transparent: shares critical information, speaks with candor, contributes constructively
• Focused: quick learner, strategically prioritizes work, committed
• Leadership ability: strong communicator, decision-maker, collaborative
• Problem solver: analytical-minded, challenges existing processes, critical thinker

At GE Aerospace, we have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen. Here, you will have the opportunity to work on really cool things with really smart and collaborative people. Together, we will mobilize a new era of growth in aerospace and defense. Where others stop, we accelerate.

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