Lead Machine Learning Engineer

Optimum Solutions; United States; Hybrid; USD 42,000 - 74,000; Full time

Job summary

Optimum Solutions seeks a Lead Machine Learning Engineer to design and build an enterprise ML platform on Databricks, including feature stores, pipelines, governance, and scalable inference solutions. You will lead cross-functional teams, drive MLOps practices, and mentor engineers and data scientists.

The role requires 8+ years in ML/Data Science, strong Python/SQL, and Azure DevOps experience, with hybrid work across India. Collaborative leadership and governance focus are essential.

Qualifications

• 8+ years of experience in ML / Data Science / MLOps / ML Engineering
• Strong hands-on Databricks MLOps experience
• Expert-level Python & SQL
• MLflow
• Unity Catalog
• Delta Lake
• Databricks Workflows & Jobs
• Model Registry
• CI/CD & Continuous Training pipelines
• Production Feature Store & Feature Engineering
• Strong Azure Cloud & Azure DevOps experience
• ML lifecycle management, monitoring, drift, lineage & reproducibility
• Strong technical leadership and stakeholder management

Responsibilities

• Lead the architecture and implementation of the enterprise ML platform on Databricks.
• Build end-to-end MLOps workflows covering development, training, testing, registration, deployment, monitoring, retraining, and rollback.
• Design and implement enterprise Feature Stores, feature pipelines, governance, lineage, versioning, and reuse.
• Productionize ML/Data Science models and develop scalable batch and real-time inference solutions.
• Implement model monitoring, data quality, drift detection, explainability, alerting, and operational dashboards.
• Establish standards for security, governance, observability, reliability, reproducibility, and lineage.
• Collaborate with Data Scientists, Data Engineers, Cloud, Architecture, Security, Risk, and Operations teams.
• Mentor engineers and Data Scientists while driving strong software and ML engineering practices.

Skills

ML/DL

Databricks MLOps

Python & SQL

MLflow

Unity Catalog

Delta Lake

Databricks Workflows/Jobs

Model Registry

CI/CD & CT pipelines

Production Feature Store

Azure Cloud & DevOps

ML lifecycle management

Leadership & stakeholder mgmt

Job description

We're Hiring | Lead Machine Learning Engineer Databricks

Location: Hybrid (Chennai/Bangalore/Pune/Hyderabad)/Remote

Experience: 8+ Years

Department: AI/ML CoE - Machine Learning

Employment Type: Full-Time

We are looking for an experienced Lead Machine Learning Engineer to lead the design, implementation, and evolution of an enterprise-grade ML Platform and Feature Store on Databricks.

Key Responsibilities

• Lead the architecture and implementation of the enterprise ML platform on Databricks.
• Build end-to-end MLOps workflows covering development, training, testing, registration, deployment, monitoring, retraining, and rollback.
• Design and implement enterprise Feature Stores, feature pipelines, governance, lineage, versioning, and reuse.
• Productionize ML/Data Science models and develop scalable batch and real-time inference solutions.
• Implement model monitoring, data quality, drift detection, explain ability, alerting, and operational dashboards.
• Establish standards for security, governance, observability, reliability, reproducibility, and lineage.
• Collaborate with Data Scientists, Data Engineers, Cloud, Architecture, Security, Risk, and Operations teams.
• Mentor engineers and Data Scientists while driving strong software and ML engineering practices.

Must-Have Skills

• 8+ years of experience in ML / Data Science / MLOps / ML Engineering
• Strong hands-on Databricks MLOps experience
• Expert-level Python & SQL
• MLflow
• Unity Catalog
• Delta Lake
• Databricks Workflows & Jobs
• Model Registry
• CI/CD & Continuous Training (CT) pipelines
• Production Feature Store & Feature Engineering
• Strong Azure Cloud & Azure DevOps experience
• ML lifecycle management, monitoring, drift, lineage & reproducibility
• Strong technical leadership and stakeholder management

Preferred

• Databricks Certifications
• Azure Certifications
• Machine Learning Engineering Certifications
• Experience building enterprise AI/ML platforms
• Experience with large-scale production ML systems

Note

• Only candidates with strong exp in ML will be considered.
• Candidates from core Data Scientist/Data Engineer is not suitable