Databricks Architect-MLOps (Banking / Model Risk Focus) in NYC, NY (Hybrid role)

Role: Databricks Architect – MLOps (Banking / Model Risk Focus)

Location: NYC, NY (Hybrid role- 3days onsite in a week)

Duration: Long Term

Job description:

We are seeking a Databricks Architect with deep MLOps expertise to lead the design and implementation of scalable machine learning platforms within a banking environment. This role will focus on building production-grade ML pipelines, governance frameworks, and model lifecycle management aligned with model risk management (MRM) standards.

Key Responsibilities:

• Architect and implement end-to-end MLOps frameworks on Databricks
• Design scalable ML pipelines using:
• Databricks Workflows
• MLflow (experiment tracking, model registry, deployment)
• Unity Catalog (governance, lineage, access control)
• Build and operationalize:
• CI/CD pipelines for ML models
• Automated model training, validation, and deployment workflows
• Establish model monitoring and observability (drift, performance, bias)
• Implement governance controls aligned with banking / regulatory requirements
• Partner with data science, risk, and engineering teams to productionize models
• Define best practices for feature engineering, versioning, and reproducibility.

Qualifications we seek in you!

Required Qualifications

• Experience in data/ML engineering or architecture
• Hands-on Databricks experience
• Strong expertise in MLOps frameworks and production ML systems
• Deep experience with:
• MLflow
• Python (PySpark, Pandas, scikit-learn)
• Spark-based data processing
• Experience designing enterprise-grade data platforms (lakehouse architecture)
• Proven ability to deploy ML models into production environments

Preferred Qualifications/ Skills

• Experience in banking or financial services.
• Strong understanding of Model Risk Management (MRM), including:
• Model validation workflows
• Auditability and documentation standards
• Regulatory expectations (SR 11-7, etc.)
• Familiarity with:
• Feature stores (Databricks Feature Store)
• Real-time / batch inference patterns
• Data governance and lineage tracking