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Tier-1 brand, mid-level ML title, metro location, and broad skillset make competition high.
Core ML/DL skills transfer easily across industries despite some business-use-case specifics.
Explicit 2-5 years requirement plus mandatory ML stack (Python, PyTorch/TensorFlow) increases strictness.
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Design, develop, train, evaluate, and optimize machine learning models including classical ML, deep learning, and Generative AI for diverse business applications.
Engineer impactful features from raw data and select relevant features to improve model performance and interpretability.
Develop end-to-end ML pipelines and collaborate with engineers to deploy models in production environments.
Bachelor's Degree or equivalent combination of coursework and experience.
2-5 years of relevant work experience in machine learning.
Strong Python programming skills.
Experience with ML frameworks such as PyTorch or TensorFlow and understanding of classical ML algorithms.
Practical experience in building and deploying machine learning models across multiple algorithms and tasks (classification, regression, clustering).
Familiarity with Generative AI technologies (e.g., Transformers, BERT, GPT models) and ability to apply them in real-world solutions.
Data-driven approach with capability to conduct feature engineering, exploratory data analysis, and use model interpretability tools like SHAP.