Elevance Health

Machine Learning Scientist

Elevance Health

full-time

Posted on:

Location: Illinois, Ohio, Virginia • 🇺🇸 United States

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Salary

💰 $138,160 - $207,240 per year

Job Level

Mid-LevelSenior

Tech Stack

CloudKafkaRaySparkSQL

About the role

  • Responsible for Artificial Intelligence (AI) scientific and statistical methods to assist with product creation, development and improvement.
  • 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.

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.
  • 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.
  • Proven outcomes by shipping AI products with measurable clinical and business impact.
  • Experience developing and maintaining infrastructure systems that connect internal data sets.
  • Experience creating new data collection frameworks for structured and unstructured data.
  • Experience designing horizontal capabilities such as RAG, evaluations-as-a-service, prompt/version control, guardrails, feature, and vector stores.
  • Experience delivering end-to-end ML systems (XGBoost / LightGBM) and LLM systems with clear SLOs.
  • Experience with cloud lakehouse (Databricks / Spark, SQL), streaming (Kafka/Kinesis), and API-first approaches.
  • Experience with serving technologies (vLLM / Triton / KServe / Ray / SageMaker).
  • Experience with MLOps/LLMOps tools like MLflow, CI/CD, and IaC.
  • Knowledge of observability, drift detection, hallucination rates, and maintaining SLOs/SLAs.
  • Knowledge of data leadership strategies including data contracts, quality SLAs, and FHIR-aware design for PHI/PII.
  • Experience with embedding/vectorization strategies.
  • Experience developing Responsible AI frameworks including fairness/robustness evaluations, red-teaming, and model risk management.
  • Knowledge of audit readiness (HIPAA, SOC 2, HITRUST).
  • Ability to define visions and OKRs for strategy and portfolio management and influence VP/C-suite.
  • Mentoring and overseeing Agile/SAFe delivery across multiple teams.
  • This position is not eligible for current or future visa sponsorship.
  • 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.