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Develop and implement AI/ML models, including supervised, unsupervised, and deep learning algorithms.
Build and optimize end‑to‑end machine learning pipelines, including data preprocessing, feature engineering, model training, validation, and deployment.
Work with NLP, Computer Vision, LLMs, and other AI domains as required.
Develop high‑quality, scalable code using Python and relevant AI/ML frameworks.
Collaborate with cross‑functional teams (Data Engineering, Product, Architecture) to design AI‑driven solutions.
Conduct research, evaluate new technologies, and recommend improvements to existing models and processes.
Monitor model performance and implement enhancements to ensure accuracy and reliability.
Prepare technical documentation, reports, and model explainability outputs.
5-8 years of hands‑on experience in Artificial Intelligence and Machine Learning.
Strong proficiency in Python and libraries such as NumPy, Pandas, Scikit‑learn, TensorFlow, PyTorch, Keras.
Experience with AI domains such as NLP, Computer Vision, Generative AI, LLMs, or Recommendation Systems.
Solid understanding of ML concepts, data structures, algorithms, and statistical methods.
Experience deploying models using Docker, REST APIs, cloud platforms (AWS/Azure/GCP).
Familiarity with MLOps tools (MLflow, Kubeflow, Airflow) is a plus.
Strong problem‑solving abilities and the ability to work in a fast‑paced, dynamic environment.
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