Lead Machine Learning Engineer (Azure ML & MLOps)

Senior / Lead Machine Learning Engineer (Azure ML & MLOps) Location: Bengaluru (Work from Office) Contract Duration: 6 Months Experience: 10+ Years Role Overview We are looking for an experienced Machine Learning Engineer to design, develop, and deploy scalable AI/ML solutions in an enterprise environment. The ideal candidate will have strong hands-on experience in building, training, optimizing, and operationalizing machine learning models, along with expertise in Azure Machine Learning and MLOps practices. This role requires deep technical expertise in statistics, mathematics, algorithms, data modeling, and software engineering principles to build high-performance, production-ready ML systems. Key Responsibilities • Transform data science prototypes into scalable production-grade ML systems. • Design and implement end-to-end machine learning solutions. • Research, evaluate, and implement appropriate ML algorithms and frameworks. • Develop ML applications as per business requirements. • Select and preprocess appropriate datasets and data representation methods. • Conduct ML experiments and statistical analysis for model evaluation and fine-tuning. • Train, retrain, and optimize models for performance and accuracy. • Extend and customize existing ML libraries and frameworks when required. • Implement and manage MLOps pipelines for model deployment, monitoring, and lifecycle management. • Collaborate with cross-functional teams to deliver AI-driven solutions. • Stay updated with the latest advancements in machine learning and AI technologies. Required Skills & Experience • 10+ years of overall experience in software engineering, with strong focus on Machine Learning. • Proven experience as a Machine Learning Engineer in enterprise environments. • Strong hands-on experience with Azure Machine Learning and MLOps. • Deep understanding of data structures, data modeling, and software architecture. • Strong knowledge of mathematics, probability, statistics, and ML algorithms. • Proficiency in Python (mandatory) and working knowledge of R. • Experience with ML frameworks such as Keras, PyTorch, and libraries like scikit-learn. • Experience in building production-ready ML systems. • Strong analytical and problem-solving skills. • Excellent communication and teamwork abilities.