Senior Data Scientist | Machine Learning Engineer (MLE)

You are an experienced Data Scientist with expertise in ML/DL, model lifecycle management, and MLOps tools such as MLflow and Kubeflow. You are proficient in Python, TensorFlow, PyTorch, Scikit-learn, and Hugging Face models. Your strong experience in NLP, fine-tuning transformer models, and dataset preparation will be valuable. Key Responsibilities: - Design and implement end-to-end ML pipelines from data ingestion to production - Develop, fine-tune, and optimize ML models for high performance and scalability - Compare and evaluate models using key metrics such as F1-score, AUC-ROC, and BLEU - Automate model retraining, monitoring, and drift detection - Collaborate with engineering teams to ensure seamless ML integration - Mentor junior team members and enforce best practices Qualifications Required: - Total of 4 years of experience, with at least 3 years in Data Science roles - Hands-on experience with cloud platforms like AWS, GCP, Azure, and scalable ML deployment tools like Sagemaker and Vertex AI - Familiarity with containerization tools such as Docker and Kubernetes, as well as CI/CD pipelines - Knowledge of distributed computing (Spark, Ray), vector databases (FAISS, Milvus), and model optimization techniques like quantization and pruning - Experience with model evaluation, hyperparameter tuning, and model monitoring for drift detection Please note: The job is full-time with a day shift schedule from Monday to Friday. The work location is in person.,