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Tier-1 brand, mid-level ML role, metro location, and broad skills requirements create high competition.
Core ML engineering skills transfer across industries, but enterprise-scale systems require moderate domain familiarity.
Explicit 5–10 years requirement plus mandatory ML, data pipelines, and cloud platform skills imply high strictness.
Design and develop scalable AI/ML models, data pipelines, and intelligent systems to solve complex business problems.
Provide technical leadership in AI solution design, collaborating with cross-functional teams and mentoring junior members.
Establish standards and best practices for model development, ensure performance, reliability, and alignment with enterprise standards.
Bachelor’s or Graduate Degree in Computer Science, Data Science, AI, Engineering, or related discipline, or equivalent experience.
5-10 years of experience in machine learning, data science, or software engineering, preferably in large-scale or enterprise environments.
Proficiency with AI/ML modeling (regression, classification, ensemble methods), Python, SQL, distributed computing (e.g., PySpark), and cloud platforms (Azure, AWS, GCP).
Work Experience Required: 5-10 years in relevant fields.
Experienced in implementing end-to-end AI/ML pipelines from data ingestion to deployment in cloud-based and distributed environments.
Capable of aligning technical AI solutions with business needs and translating model outputs into actionable outcomes.
Comfortable driving complex projects independently while collaborating with global teams and mentoring junior staff.