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Lead Machine Learning Engineer
  • Posted 12 days ago
  • Be among the first 10 applicants

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

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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

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