Design, develop, and deploy end-to-end machine learning and deep learning models for real-world business problems
Build scalable solutions for large-volume data processing (structured & unstructured)
Develop and optimize Generative AI applications using LLMs (e.g., RAG pipelines, copilots, summarization, Q&A systems)
Implement predictive analytics models such as classification, regression, clustering, and anomaly detection
Collaborate with cross-functional teams (product, data engineering, business stakeholders)

4 to 15 years of experience in Machine Learning
Strong foundation in machine learning algorithms (supervised & unsupervised)
Experience with anomaly detection, time-series, and predictive modeling
Proficiency in Python and ML libraries (Scikit-learn, XGBoost, PyTorch/TensorFlow)
Experience with data preprocessing, feature engineering, and model evaluation
Hands-on experience with LLMs (OpenAI, Claude, Hugging Face, etc.)
Strong understanding of Retrieval-Augmented Generation and prompt engineering
Experience building GenAI applications (chatbots, document Q&A, summarization systems)
Experience working with large datasets (batch + streaming)
Knowledge of data pipelines and tools (Spark, Airflow, or similar)
Familiarity with cloud platforms (Azure, AWS, or GCP)

Machine Learning Engineer

Key skills