Senior Machine Learning Engineer (ML Ops)

About the role

We are seeking a Senior Machine Learning Engineer to design, develop, deploy, and operate scalable ML solutions for enterprise applications such as document processing, anomaly detection, and intelligent automation.

Key responsibilities

• Define ML problem statements, data requirements, and solution approaches.
• Build reliable data pipelines and ensure data quality and preprocessing.
• Develop, train, evaluate, and optimize Machine Learning and Deep Learning models.
• Deploy scalable ML models and inference services into production.
• Monitor model performance, data quality, and model/data drift.
• Implement MLOps pipelines, CI/CD, model versioning, and automated deployment.
• Ensure ML solutions meet security, privacy, governance, and compliance requirements.
• Optimize ML infrastructure for performance, scalability, and cost.
• Integrate ML models with applications through REST APIs and enterprise systems.
• Prepare technical documentation, model cards, experiment documentation, and deployment guides.
• Collaborate with software developers, data engineers, and IT teams for production integration.
• Identify opportunities to improve MLOps processes, model performance, and operational efficiency.

Required profile

• 5+ years of applied Machine Learning / AI experience.
• Bachelor's degree in Computer Science, AI, Data Science, Data Engineering, or related field; Master's preferred.
• Strong Python programming skills.
• Experience with scikit-learn, TensorFlow or PyTorch.
• Proficiency in SQL and data processing.
• Experience building data pipelines and ensuring data quality.

Required skills

• Machine Learning and Deep Learning model development and evaluation.
• MLOps, CI/CD, model deployment and monitoring.
• Model and data drift monitoring.
• REST APIs integration.
• Cloud ML / ML infrastructure experience.