Description
We are seeking a Senior Machine Learning Engineer, Decision Intelligence to join our team. As a hands-on individual contributor, you will be responsible for building, deploying, and operating ML and decisioning pipelines for the NBA Decision Intelligence Platform. Your focus will be on production pipeline development, MLOps, feature engineering, scoring workflows, monitoring, and optimization-aware decisioning.
You will work closely with ML engineers, data engineers, platform engineers, product owners, and decision engine teams to deliver reliable, scalable, and auditable production systems. You will help ensure the platform selects the right action for the right member while respecting clinical eligibility, suppression rules, channel constraints, program goals, and operational capacity.
Required Qualifications
- 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, with an emphasis on data-intensive platforms, recommendation systems, optimization engines, or simulation frameworks serving millions of users
- 2+ years of hands-on experience implementing reinforcement learning, operations research methods, or simulation-driven decision systems in production
- Deep familiarity with Markov Decision Processes, Bellman-equation-based value estimation, reward or objective shaping, exploration-exploitation tradeoffs, and constraint formulation in real-world decision systems
- Demonstrated ability to diagnose failure modes in learned or optimized policies
- Proficiency in Python 3.x; experience with PyTorch or TensorFlow for policy network or learned model implementation
- Experience with Ray RLlib or equivalent distributed computation frameworks for large-scale training or optimization
- Experience with Databricks, PySpark, and Delta Lake for large-scale ML or data pipelines processing tens of millions of records
- Experience with MLflow for experiment tracking, model registry, and artifact management
- Experience with shipping systems that operate reliably under production load
Preferred Qualifications
- Experience with multi-agent RL frameworks or multi-agent simulation and coordination methods
- Familiarity with operations research methods applicable to constrained sequential decisioning
- Experience operating decision or optimization systems in regulated domains
- Experience building simulation environments using Gymnasium, SimPy, AnyLogic, or equivalent frameworks for policy evaluation and backtesting
- Familiarity with event-driven feedback loops and how disposition signals feed retraining or re-optimization pipelines
- OpenTelemetry instrumentation experience for ML or optimization pipeline observability
Additional Information
- Remote/Hybrid work style, preferably Boston, MA
- Occasional travel to Humana's offices for training or meetings may be required
- Typical business hours are Monday-Friday, 8 hours/day, 5 days/week
- The compensation range for this role is $106,900 - $147,000 per year
- This job is eligible for a bonus incentive plan
Benefits
- Medical, dental, and vision benefits
- 401(k) retirement savings plan
- Time off, including paid time off, company and personal holidays, paid parental and caregiver leave
- Short-term and long-term disability
- Life insurance