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Tier-1 brand, Bangalore mid-level ML role with popular skills drives high competition despite domain specificity.
Requires automotive manufacturing experience plus ML domain knowledge, limiting transferability across industries.
Multiple explicit year requirements plus mandatory manufacturing domain and ML/MLOps skills create high shortlisting rigidity.
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Lead end-to-end AI/ML projects from problem identification through design, development, deployment, and maintenance in Manufacturing Engineering and Operations.
Develop and fine-tune ML models for classification, regression, clustering, and recommendation systems with measurable impact on manufacturing processes.
Collaborate with cross-functional teams to deploy and monitor AI solutions, ensuring compliance with data security and regulatory standards.
Bachelor's or Master's degree in Mechanical, Automobile, Production, Mechatronics Engineering or similar.
Minimum 5 years of experience in Automotive Manufacturing or Manufacturing Engineering.
At least 1 year of experience implementing AI/ML solutions in automotive use cases with a minimum of 2 end-to-end projects in text or image data domains.
Proficiency in Python programming, ML/DL frameworks (Scikit-learn, TensorFlow, PyTorch, XGBoost), MLOps tools, SQL/NoSQL databases, and understanding of ML model evaluation and data handling.
Experienced in applying ML methodologies specifically within manufacturing or automotive domains to solve complex engineering problems.
Capable of managing full ML project lifecycle including model deployment and monitoring in production environments with cross-functional collaboration.
Strong technical expertise in ML frameworks, data engineering, and MLOps workflows combined with a solid foundation in statistics and mathematics.