Senior ML/AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop the decision-making and feedback framework connecting model scores to actions, encompassing action selection, holdout and experiment assignment, outcome capture, and lift measurement.

• Create and implement event-driven, real-time integrations between model outputs and operational systems, which include streaming pipelines, schemas, replay, ordering, and failure management.

• Monitor and manage costs associated with compute, streaming, inference, and LLM through budgets and alerts.

• Deploy, oversee, and retrain production ML models by utilizing CI/CD, model registries, and alert systems for drift, coverage, and calibration.

• Develop and enhance predictive models utilizing healthcare claims, authorization, and operational data.

• Scale AWS-native infrastructure in conjunction with the Databricks lakehouse, employing infrastructure as code, IAM, secure data management, containerized inference, and managed foundation-model services under PHI regulations.

• Advance the feature store and data assets towards real-time features.

• Take ownership of production GenAI applications, including LLM pipelines and agentic workflows, ensuring evaluation, retrieval, guardrail, and cost management.

• Collaborate with data scientists, data engineering, and software engineering on production models, pipelines, interfaces, and contracts.

• Set engineering standards through code reviews, automated testing, reproducibility, documentation, and disciplined releases.

• Guide data scientists in production best practices.

• Report to the Director of AI & Decision Intelligence while working closely with clinical and operations partners.

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.

• Over 5 years of experience in ML engineering, MLOps, or data science, including a minimum of 3 years operating ML systems in production.

• Demonstrated production experience with Databricks, PySpark, Delta Lake, and MLflow.

• Proven production experience with AWS data and ML services and infrastructure as code (Terraform, CDK, or CloudFormation).

• Practical experience in designing and managing event-driven or streaming systems (Kinesis, Kafka, or similar) with schema or contract management.

• Proficient in Python and SQL.

• Experience in building and evaluating ML models using scikit-learn, XGBoost, or PyTorch.

• Familiarity with CI/CD for ML workloads along with model and pipeline monitoring.

• Willingness and capability to travel up to 10% as necessary for on-site meetings, team collaboration, and company events.

• Preferred: experience with recommendation, decision-making, or experimentation systems; dbt; healthcare data and PHI management; containerized model serving; Amazon Bedrock or managed foundation-model platforms under a HIPAA BAA; agentic frameworks; retrieval systems; LLM applications, evaluation, and guardrails.

🏝️ Benefits

• Engaging work in a mission-driven environment.

• Remote-first work culture with opportunities for a hybrid work model in Nashville.

• Generous paid time off (PTO) and holiday policies.

• Paid parental leave.

• Flexibility in work-life balance and autonomy.

• Comprehensive medical, dental, vision, life, and disability insurance from Day 1.

• Wellness resources available.

• Employer contribution to HSA.

• 401(k) plan with employer matching.

• Inclusive community and collaborative work atmosphere.