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Junior

Associate Machine Learning Engineer-1

Confirmed live in the last 24 hours

The Goodyear Tire \u0026 Rubber Company

The Goodyear Tire \u0026 Rubber Company

IN Hyderabad
On-site
Posted April 28, 2026

Job Description

To join our team, you will need:

Education:

M.Sc. in Data Science, Mathematics, Computer Science, or related technical field


Languages:

You are fluent in English.

Experience:

  • 3+ years of experience in developing machine learning and advanced data analysis solutions on large data sets
  • At least one experience in the industrial sector, involving IoT and sensor data

Skills & Qualifications:

Demonstrated knowledge in Applied Mathematics (statistics, linear algebra, optimization)

Demonstrated experience with:

  • Development and deployment of production level Data Science and AI solutions (e.g. machine learning, data fusion, reinforcement learning, machine learning engineering)
  • Data science and machine learning libraries (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, HuggingFace)
  • Software engineering tools and practices (Python, Git, CI/CD, automated testing)
  • System infrastructure in Linux/Windows (Bash, PowerShell, Docker, HPC)
  • Cloud platform technology
  • Databases and data management (SQL, cloud DBs, data lakes)

Ability to work independently as well as contribute in a collaborative environment.

Willingness to explore and learn new technologies.

Goodyear is one of the world's largest tire companies. It employs about 68,000 people and manufactures its products in 51 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 Goodyear.com.

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

machine learning