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Mid-level, generalist ML role in Mumbai with broad skillset and metro location creates high applicant competition.
Technical ML engineering skills transfer across industries, though retail domain experience is preferred.
Explicit 2–5 years requirement plus mandatory production ML and specific framework skills increases strictness.
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Design, build, evaluate, and deploy ML and Deep Learning models for retail and e-commerce use cases such as classification, regression, forecasting, anomaly detection, churn prediction, and recommendation systems.
Translate ML research/prototypes into production-ready, scalable, and reliable code integrated via REST APIs within enterprise SaaS platforms.
Support model deployment, monitoring, and maintenance using MLOps tools, and contribute to continuous improvement of ML engineering practices and internal tools.
2 to 5 years of experience as a Data Analyst with a focus on ML model development.
Strong proficiency in Python and SQL for ML modeling and data workflows.
Hands-on experience with ML/DL algorithms and frameworks (Scikit-learn, TensorFlow/Keras or PyTorch, XGBoost).
Work mode: Full-time, onsite in Mumbai (Saki Vikar) with Monday to Friday workdays.
Experienced in delivering at least one ML use case into production beyond prototype or notebook stage, understanding model serving and monitoring.
Strong foundation in statistics, feature engineering, model validation, and hyperparameter tuning applicable in real-world scenarios.
Familiarity or willingness to deepen skills in MLOps practices such as model versioning, experiment tracking, containerization, and deployment workflows.