AI/ML Engineer/Sr Engineer/Lead

As an AI/ML Engineer, your role involves designing, building, and deploying production-grade machine learning systems with a focus on model development and MLOps practices. You will ensure that ML solutions are scalable, maintainable, and performance optimized. **Key Responsibilities:** - Design and implement ML models for various purposes such as classification, regression, clustering, Recommendation System, Anomaly Detection, Neural Networks, NLP, and Comp Vision Models - Package models and deploy them into production environments using CI/CD workflows - Develop and manage ML pipelines for data preprocessing, training, testing, and serving - Monitor model performance in production (latency, drift, accuracy) and retrain when necessary - Collaborate with data engineers, MLOps engineers, and DevOps for smooth deployments - Support versioning of models, datasets, and configurations - Participate in performance tuning, experiment tracking, and governance enforcement **Qualifications Required:** - Strong programming skills in Python, with experience in Scikit-learn, XGBoost, or TensorFlow/PyTorch - Experience building and deploying models using Flask, FastAPI, or Streamlit - Solid grasp of MLOps concepts including CI/CD for ML, model versioning and registry, data versioning, monitoring, and retraining workflows - Comfortable working with containerization (Docker) and deployment on cloud platforms (AWS, Azure, or GCP) - Good understanding of model explainability, fairness, and data privacy **Nice To Have:** - Familiarity with Airflow, Kubeflow, or Prefect for orchestration - Exposure to feature stores and drift detection tools - Experience with NLP (LLMs, Transformers) or time series forecasting - Understanding of model caching, load testing, and API security for ML services (Note: Domain Knowledge in Financial Services, especially Capital Markets, is an added advantage),