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Popular ML role, metro Chennai location, and broad GenAI/MLOps requirements increase applicant density.
Core ML and GenAI skills are transferable, though transformer domain experience adds moderate industry specificity.
No explicit years but multiple mandatory technical skills (Python, cloud, MLOps) create moderate screening filters.
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Develop and support end-to-end AI/ML pipelines for transformer-related design, operations, manufacturing, and services, including data ingestion, model training, evaluation, and deployment.
Architect and integrate cloud-based AI/ML and Generative AI resources, including LLM-based assistants and retrieval-augmented generation systems, to enhance engineering and operational workflows.
Implement and support MLOps and GenAIOps practices including automation, monitoring, versioning, lifecycle management, and testing of AI/ML solutions in collaboration with cross-functional teams.
Bachelor's (B.E/B.Tech) or Master's degree in Computer Science, Data Science, AI, Software Engineering, or related field.
Hands-on experience (academic, internship, or early professional) building AI/ML pipelines.
Proficiency in Python and associated ML/data libraries (scikit-learn, TensorFlow/PyTorch, NumPy, Pandas).
Experience with cloud platforms (preferably Microsoft Azure), AI/ML services, and managing build agents including self-hosted environments.
Experience or exposure to Generative AI concepts including LLMs, embeddings, prompt engineering, and retrieval-augmented generation systems.
Ability to translate engineering/operational requirements into scalable AI solution designs and collaborate closely with domain experts and engineers in a co-development environment.
Familiarity with MLOps, GenAIOps, CI/CD pipelines, containerization, and understanding of multi-step agentic AI workflows oriented towards transformer or industrial domain applications.