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Tier-1 brand, mid-seniority generalist ML role, and metro location increase candidate competition.
Role demands specialized ML/AI and production MLOps expertise, reducing cross-industry interchangeability.
Explicit 5+ years, required production ML experience and broad framework expertise enforce strict screening.
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Design, develop, and deploy scalable machine learning models and end-to-end ML workflows including data preparation, feature engineering, deployment, and optimization.
Build ML capabilities focused on recommendation systems, personalization, predictive modeling, NLP, Generative AI, and Large Language Models.
Collaborate cross-functionally with Data Engineers, ML Engineers, Product Managers, and business teams to deliver data-driven solutions and mentor junior team members.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative fields.
5+ years of experience in building data science models and machine learning solutions, including development and production deployment.
Proficiency with Python, R, Scala or similar languages and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, XGBoost, Keras, and Spark ML.
Experience with scalable ML architectures, MLOps concepts, working on large-scale datasets, and end-to-end ML lifecycle (feature engineering, training, validation, deployment, monitoring).
Experienced in building personalization, customer growth, advertising, content recommendation, or large-scale consumer platform ML solutions.
Comfortable applying advanced ML techniques including Regression, Classification, Time Series, Causal Inference, Deep Learning, NLP, LLMs, Reinforcement Learning, and Model Optimization.
Able to translate research and modern AI/GenAI frameworks into practical, scalable business solutions within a collaborative, cross-functional environment.