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Job Description
Structured overview of role & requirementsAbout This Role
Develop, validate, and deploy machine learning and AI models specifically for automotive or manufacturing business challenges such as predictive maintenance and supply chain optimization.
Design and implement end-to-end data science pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment on cloud platforms (Azure preferred, AWS, GCP).
Build and operationalize Agentic AI systems (autonomous agents, multi-agent workflows, LLM-based reasoning) and integrate with IoT, telematics, MES, ERP, and connected vehicle platforms.
Minimum Requirements
Mandatory programming skill: Python with libraries Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
Experience applying statistical techniques including hypothesis testing, regression, Bayesian methods.
Domain experience required: automotive or manufacturing, especially in predictive maintenance, quality analytics, supply chain optimization, or connected vehicle analytics.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Demonstrates strong expertise in applied machine learning, AI, and emerging Agentic AI frameworks relevant to real-world industrial use cases in automotive or manufacturing.
Experienced in cloud-based model deployment and building production-grade AI/ML systems, indicating operational focus and ability to scale solutions.
Skilled at communicating complex model insights effectively to non-technical stakeholders and managing cross-functional teams including data engineering and business units.