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Tier-1 brand, mid-level ML role, metro Bangalore, and broad skill requirements increase competition.
ML engineering skills are transferable across industries but require specific tooling and domain expertise.
Explicit 5–10 years and mandatory ML engineering skills make screening relatively strict.
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Design, develop, and deploy scalable AI/ML models and pipelines addressing complex business problems.
Lead technical design and implementation of AI solutions across cross-functional teams and cloud platforms.
Mentor junior members and establish best practices for model development, feature engineering, and evaluation.
Bachelor's degree or equivalent in Computer Science, Data Science, AI, Engineering, or related field.
5–10 years of experience in machine learning, data science, or software engineering in large-scale/enterprise environments.
Proficiency in Python, SQL, machine learning techniques, and experience with cloud platforms (Azure, AWS, GCP).
Experience building and maintaining scalable data pipelines and ML workflows; knowledge of distributed computing (e.g., PySpark).
Experienced in delivering enterprise-scale AI/ML solutions with end-to-end pipeline ownership.
Technically strong in both AI model development and data engineering with cloud and distributed systems expertise.
Capable of leading cross-functional collaboration and mentoring, contributing to strategy and standards for AI initiatives.