ML Ops Engineer

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities. Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth.
We are looking for a skilled ML Ops Engineer with strong experience in deploying and managing machine learning models in production environments. The ideal candidate must have hands-on expertise in ML Ops practices, Databricks, and strong SQL skills (mandatory) along with good communication abilities to collaborate effectively with cross-functional teams.
Responsibilities
Design, implement, and manage end-to-end ML pipelines for model training, testing, and deployment
Deploy and maintain machine learning models in production environments
Develop and optimize data pipelines using SQL (mandatory)
Work closely with Data Scientists and Data Engineers to operationalize ML models
Build and maintain CI/CD pipelines for ML workflows
Monitor model performance and ensure scalability and reliability
Utilize Databricks for data engineering, model development, and deployment
Ensure best practices in data governance, versioning, and reproducibility
Troubleshoot and resolve production issues efficiently
Strong experience in ML Ops (Model Deployment, Monitoring, CI/CD)
Hands-on experience with Databricks
Strong SQL expertise (mandatory) for data manipulation and pipeline development
Good communication and stakeholder management skills
Experience with cloud platforms (AWS/Azure/GCP)
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
4+ years of relevant experience in ML Ops / Data Engineering / ML Engineering