Machine Learning Engineer

• Design, develop, and deploy scalable Machine Learning models for real-world business problems
• Work with large-scale structured and unstructured datasets
• Build and maintain end-to-end ML pipelines (data ingestion, feature engineering, model training, evaluation, and deployment)
• Collaborate closely with Data Engineers, Data Scientists, and Product teams
• Optimize model performance, accuracy, and efficiency
• Implement MLOps best practices including monitoring, versioning, and retraining
• Ensure compliance with security, governance, and regulatory standards
• Participate in code reviews, design discussions, and technical documentation

Do you have experience in Statistics?, * 6-11 years of overall experience with strong focus on Machine Learning Engineering

• Strong programming experience in Python
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn
• Experience with data processing frameworks (Spark, Pandas, NumPy)
• Strong understanding of ML algorithms, statistics, and model evaluation techniques
• Experience deploying models using REST APIs, Docker, Kubernetes
• Solid knowledge of SQL and working with large databases
• Experience with cloud platforms (AWS, Azure, or GCP)
• Strong problem-solving and communication skills, * Prior experience working with financial services or banking clients
• Experience with NLP, Time Series, or Recommendation Systems
• Exposure to CI/CD pipelines and automation tools
• Knowledge of data governance and model risk management