ML Architect

Job Role: ML Architect Experience: 12+ years Locaton: NYC Reequired Skills 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: o Databricks Workflows o MLflow (experiment tracking, model registry, deployment) o Unity Catalog (governance, lineage, access control) Build and operationalize: o CI/CD pipelines for ML models o 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: o MLflow o Python (PySpark, Pandas, scikit-learn) o 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: o Model validation workflows o Auditability and documentation standards o Regulatory expectations (SR 11-7, etc.) Familiarity with: o Feature stores (Databricks Feature Store) o Real-time / batch inference patterns o Data governance and lineage tracking