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1 Day ago

Senior Machine Learning Engineer

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Bangalore, KA, India
Information Technology
Full-Time
The Goodyear Tire & Rubber Co.

Overview

Staff Data Scientist/Machine Learning Engineer

Are you interested in an exciting opportunity to drive success with data? The Data Driven Engineering team at Goodyear in the Innovation Centers in Colmar-Berg, Luxembourg and Akron, Ohio, United States and in the Goodyear Technical Center in Hyderabad, India does just that. The team is focused on developing tools, applications and insights in support of the virtual tire development mission that seeks to develop a virtual framework for tire design and tire performance prediction with the aim to reduce design iterations and speed up product development.

What You Will Do

The incumbent will join the Data Driven Engineering group at the Goodyear Technical Center in Hyderabad, India that focuses on developing AI methodologies for virtual tire development process. In particular:

  • Develop AI solutions from inception to deployment which support various processes of the Data Driven Engineering group.
  • Independently perform tasks to support large-scale data driven engineering initiatives in our global organization. Tasks will include data exploration and transformation, feature generation, modeling, data visualization.
  • Develop an understanding of the business, technology, manufacturing processes, and data driven engineering-related topics such as data systems (data sources, data gathering, data storage) and business analytics (business reporting procedures and metrics).
  • Work closely with other data scientists, data engineers, and cloud architects in scaling prototype data models into production-quality digital solutions
  • Share and present your ideas and successes with business stakeholders, subject matter experts, and IT professionals throughout the company.
  • Have an impact by helping us drive “best data driven engineering practices” within the Global Technology organization.
  • Be a part of cross-functional teams working together to deliver impactful results.

What We Expect

M.Sc. in Data Science, Mathematics, Statistics, or similar technical field

Ph.D. is preferred or equivalent experience.

Experience:

Minimum 5+ years of experience in Machine Learning and advanced data analysis(Data Engineering & Data Science) on large data sets is an asset.

At least one year experience in the automotive or an industrial sector(Manufacturing or Energy) with focus on structures, vibrations and acoustics fields.

Skills & Qualifications:

  • Demonstrated knowledge in several subjects, in some of the following areas: Applied Mathematics. Machine learning (supervised, unsupervised learning, deep neural networks, model explain ability, feature engineering, dimensionality reduction, data viz), Advanced Statistics (e.g., Bayesian inference, uncertainty quantification). Computer Science (e.g., machine learning, data architecture, data management, programming, “big data” technologies).
  • Demonstrated experience with: Python programming language, SQL, Software development tools and processes (GitHub, Docker, Kubernetes, Jenkins), Cloud platform technology (AWS or MS Azure)
  • Must be able to function independently as well as work in a team-oriented environment.
  • Good teamwork skills - ability to work in a team environment and deliver results on time.
  • Strong communication skills - capable of conveying information concisely to diverse audiences.

#Li-Hybrid

#Li-APGY


Goodyear is one of the world's largest tire companies. It employs about 63,000 people and manufactures its products in 49 facilities in 19 countries around the world. Its two Innovation Centers in Akron, Ohio, and Colmar-Berg, Luxembourg, strive to develop state-of-the-art products and services that set the technology and performance standard for the industry. For more information about Goodyear and its products, go to www.goodyear.com/corporate

Goodyear is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by law.

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