Lead Machine Learning Engineer
eidiko systems integrators private limited- Posted 12 days ago
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Job Description
Eidiko Systems Integrators, an IBM Premier Business Partner, HeadQuartered in Hyderabad, India with Delivery Centers in UAE, the US and the UK is a preferred implementation partner in Middleware, Content Management, BPM, Mobile, Collaboration and Social Business spaces. Eidiko Systems Integrators have extensive operations in the Middle East, Africa, the US and India, mostly delivering business solutions leveraging IBM technologies.
Url : https://www.eidiko.com/
We are looking for an experienced Lead Machine Learning Engineer to join our AI CoE and lead the design, implementation, and evolution of an enterprise ML platform on Databricks.
Experience: 8+ Years
Role: Lead Machine Learning Engineer
Department: AI CoE
Key Skills Required
Strong hands-on Databricks MLOps experience
MLflow, Unity Catalog, Delta Lake
Databricks Workflows & Jobs / Model Registry
Enterprise Feature Store design and implementation
Feature engineering & feature pipelines
End-to-end ML lifecycle – development, deployment, monitoring & retraining
Python & SQL
Azure Cloud & Azure DevOps
CI/CD/CT pipelines for production ML systems
ML governance, lineage, reproducibility & observability
Strong technical leadership and stakeholder management
What You'll Do
• Own and evolve the enterprise ML platform on Databricks
• Build automated ML workflows from development through deployment and monitoring
• Design and implement enterprise feature stores
• Deliver production-grade ML and Data Science solutions
• Partner with Data Scientists to productionize ML models
• Drive engineering standards, governance and continuous improvement
Education: Bachelor's or Master's degree in Computer Science – Mandatory
Databricks / Azure Certifications: Preferred
More Info
Key Skills
Feature pipelines
End-to-end ML lifecycle
CI CD CT pipelines
Enterprise Feature Store
lineage
reproducibility
MLflow
Unity Catalog
Feature engineering
Model Registry
Delta Lake
ML governance
observability
Databricks Workflows

