Senior Data Scientist-Machine Learning Engineer

Job Description

Role & responsibilities Expertise in ML/DL, model lifecycle management, and MLOps (MLflow, Kubeflow). Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and Hugging Face models. Strong experience in NLP, fine-tuning transformer models, and dataset preparation. Hands-on with cloud platforms (AWS, GCP, Azure) and scalable ML deployment (Sagemaker, Vertex AI). Experience in containerization (Docker, Kubernetes) and CI/CD pipeline. Knowledge of distributed computing (Spark, Ray), vector databases (FAISS, Milvus), and model optimization (quantization, pruning). Familiarity with model evaluation, hyperparameter tuning, and model monitoring for drift detection. Preferred candidate profile Design and implement end-to-end ML pipelines from data ingestion to production. Develop, fine-tune, and optimize ML models, ensuring high performance and scalability. Compare and evaluate models using key metrics (F1-score, AUC-ROC, BLEU etc.). Automate model retraining, monitoring, and drift detection. Collaborate with engineering teams for seamless ML integration. Mentor junior team members and enforce best practices.