Lead Machine Learning Engineer

Optimum Solutions; Chennai District, Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Optimum Solutions seeks a senior ML/DS/MLOps engineer to lead end-to-end data science solutions in enterprise environments. You will own production deployments, monitoring, and governance across Databricks platforms and CI/CD pipelines, collaborating with cross-functional teams to ensure reliability and scalability.

Ideal candidates bring hands-on Databricks MLOps experience, feature stores and governance, strong Python/SQL skills, and a proven track record of production ML systems with robust

Qualifications

• 8+ years of experience delivering ML, Data Science, MLOps or related engineering solutions.
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Responsibilities

• 8+ years of experience delivering Machine Learning, Data Science, MLOps, or closely related engineering solutions in enterprise environments.
• Proven track record of delivering end-to-end ML or Data Science solutions into production and operating them reliably.
• Deep hands-on experience implementing MLOps on Databricks and building end-to-end MLOps solutions.
• Hands-on experience designing and implementing production feature stores, feature pipelines, and feature governance.
• Strong understanding of ML lifecycle management, testing, deployment, monitoring, drift, lineage, and reproducibility.
• Demonstrated technical leadership, cross-functional collaboration, stakeholder management, and excellent written and verbal communication skills.

Skills

Python

SQL

Software engineering

System design

Tools

Databricks

MLflow

Delta Lake

Databricks Workflows & Jobs

Model Registry

CI/CD pipelines

Azure DevOps

Job description

Required Experience

• 8+ years of experience delivering Machine Learning, Data Science, MLOps, or closely related engineering solutions in enterprise environments.
• Proven track record of delivering end-to-end ML or Data Science solutions into production and operating them reliably.
• Deep hands-on experience implementing MLOps on Databricks and building end-to-end MLOps solutions.
• Hands-on experience designing and implementing production feature stores, feature pipelines, and feature governance.
• Strong understanding of ML lifecycle management, testing, deployment, monitoring, drift, lineage, and reproducibility.
• Demonstrated technical leadership, cross-functional collaboration, stakeholder management, and excellent written and verbal communication skills.

Required Skills

• Expert-level proficiency in Python, with strong SQL, software engineering, and system design fundamentals.
• Extensive hands-on experience with MLflow, Unity Catalog, Delta Lake, Databricks Workflows & Jobs, Model Registry, and CI/CD/CT pipelines for production ML systems.
• Strong experience with Azure cloud services and DevOps practices, deployment automation, monitoring, and platform operations.