Lead Engineer - Scientific Machine Learning

Key Skills

Java Programming, Python Programming, SQL, Machine learning techniques, MATLAB Programming, R Programming

Job Description

If you desire to be part of something special, to be part of a winning team, to be part of a fun team – winning is fun. We are looking forward to a Lead Engineer - Scientific Machine Learning at Eaton India Innovation Center, based in Pune, India. In Eaton, making our work exciting, engaging, meaningful; ensuring safety, health, wellness; and being a model of inclusion & diversity are already embedded in who we are - it’s in our values, part of our vision, and our clearly defined aspirational goals. Your essential responsibilities include:

• Serves as a technical lead and/or project lead for capability development and deployment on Scientific Machine Learning
• Development of ML based models for design optimization - Reduced order models
• Infrastructure development for intelligence building - data digitization, data preparation, model selection framework, model development and validation
• Infrastructure development for model deployment - Cloud platform, data streaming platform, data visulization, control models
• Intelligence development for manufacturing - exploring, developing and deploying models - Diagnostic models for quality monitoring using live manufacturing data from floor, predictive modeling for quality prediction in continuous production, prescriptive modeling for quality control
• Establish connect with Local and Global Eaton IT for standard best practices / processes
• Establish connect with external standard commercial software providers to seek support and solutions pertaining to AutoML requirements
• Contributes to the value proposition development for technical projects and programs
• Participates in internal open innovation events with businesses & other research groups
• Develops as a subject matter expert through relevant trainings and participation in relevant industry events - network and stay comtemporary on topics in their field
• Gets trained on internal systems & processes and implements them towards projects
• Becomes simulation automation expert.
• Explore advances in digital design technologies and evaluate their suitability for Eaton products.
• Works collaboratively with digital design team globally to advance the technology

The successful candidate will be responsible for leading the efforts of development of AI/ML based solutions for design, materials and manufacturing. Methods for design will include historical design data digitization (2D, 3D), data preparation methods, model selection, model development and infrastructure development for deployment. Further responsibilities will include collaboration with extended teams for seeking out applications, defining best practices, upskilling existing workforce on data engineering to help the advancement of Eaton’s digital transformation strategy.

Qualifications

• D or Master’s Degree (ME) in Mechanical, Manufacturing, Computer Science
• D with 3+ years OR Masters with 7+ years industrial experience working with Scientific Machine Learning - implementing the data analytics for engineering problems
• Excellent knowledge & Experience in machine learning models, development methods
• Working experience with demonstrated projects on application of machine learning for insights and decision making in engineering processes
• Excellent proficiency in programming languages - Python, R, MATLAB
• Working experience with AutoML tools
• Six Sigma certifications are a plus.
• Excellent communication skills in English (verbal and written)
• Awareness of product design process and manufacturing processes is a plus
• Self-motivated; Passionate to bring own ideas to applications.
• Networking ability across organization to understand critical business problems that require materials and manufacturing based solutions
• Strong oral and written communication skills. Demonstrated ability to analyze and resolve problems.
• Good interpersonal skills - flexibility to adapt to persons with different geographical, ethnic, educational backgrounds.
• Ability to document, plan, market, and execute programs. Established project management skills while handling multiple projects