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
