AI Machine Learning Scientist

AI Machine Learning Scientist

AI Machine Learning Scientist

Location: Atlanta, GA; Richmond, VA; Indianapolis, IN; Mason, OH; Chicago, IL (preferred). This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within a commuting distance from an office.

Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.

The AI Machine Learning Scientist is responsible for Artificial Intelligence (AI) scientific and statistical methods to assist with product creation, development and improvement.

How you will make an impact:

• Develops and maintains infrastructure systems that connect internal data sets.
• Creates new data collection frameworks for structured and unstructured data.
• Leads enterprise-scale AI initiatives by designing horizontal capabilities such as RAG, evaluations-as-a-service, prompt/version control, guardrails, feature, and vector stores, adopted across business units.
• Develops, analyzes, and models complex operational, clinical, and economic data, while delivering end-to-end ML systems (XGBoost / LightGBM) and LLM systems with clear SLOs.
• Architects scalable solutions including cloud lakehouse (Databricks / Spark, SQL), streaming (Kafka/Kinesis), and API-first approaches; oversees serving technologies (vLLM / Triton / KServe / Ray / SageMaker).
• Establishes and manages LLMOps / MLOps processes using tools like MLflow, CI/CD, and IaC, focusing on observability, drift detection, hallucination rates, and maintaining SLOs/SLAs.
• Implements data leadership strategies that include data contracts, quality SLAs, and FHIR-aware design for PHI/PII, with a focus on embedding/vectorization strategies.
• Develops Responsible AI frameworks including fairness/robustness evaluations, red-teaming, and model risk management, ensuring audit readiness (HIPAA, SOC 2, HITRUST).
• Defines visions and OKRs for strategy and portfolio management, orchestrating build-buy-partner decisions and optimizing ROI and FinOps, while influencing VP/C-suite and ensuring cross-functional alignment.
• Mentors principal and lead contributors, drives design reviews, and oversees Agile/SAFe delivery across multiple teams.
• Demonstrates proven outcomes by shipping AI products with measurable clinical and business impact.
• Develop experimental and analytic plans for machine learning algorithms and data modeling processes.
• Use of strong baselines.
• Determines cause and effect relations.

Minimum Requirements:

• Requires a Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree and 4 or more years of experience; or any combination of education and experience in configuration management, which would provide an equivalent background.

Preferred Skills, Capabilities & Experiences:

• Prefer Master's or PhD. degrees in a quantitative field (or equivalent) and 6+ years of experience in building production ML/LLM systems, with leadership in multi-team programs.

Job Level: Non-Management Exempt

Workshift: 1st Shift (United States of America)

Job Family: RDA > Artificial Intelligence