Senior Decision Intelligence Engineer

What you'll do

• Build, deploy, and operate ML and decisioning pipelines for the NBA Decision Intelligence Platform.
• Develop production pipelines for MLOps, feature engineering, scoring workflows, and monitoring.
• Implement reinforcement learning, operations research methods, or simulation-driven decision systems in production.
• Optimize decisioning to select actions based on clinical eligibility, suppression rules, and operational capacity.
• Manage large-scale ML data pipelines using Databricks, PySpark, and Delta Lake.
• Use MLflow for experiment tracking, model registry, and artifact management.
• Diagnose failure modes in learned policies such as instability and distributional shift.
• Instrument ML and optimization pipelines for observability using OpenTelemetry.

What we're looking for

• Bachelor's degree in computer science or a relevant field.
• 5+ years of software engineering or quantitative research experience building and operating large-scale production systems.
• 2+ years of experience implementing reinforcement learning, operations research methods, or simulation-driven decision systems in production.
• Proficiency in Python 3.x and experience with PyTorch or TensorFlow for policy network or learned model implementation.
• Experience with Ray RLlib, Databricks, PySpark, Delta Lake, and MLflow for large-scale ML pipelines and experiment tracking.
• Experience shipping systems that operate reliably under production load rather than just research or prototype work.
• Experience with multi-agent RL frameworks or multi-agent simulation and coordination methods (preferred).
• Experience operating decision or optimization systems in regulated domains like healthcare, finance, or insurance (preferred).