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Elevance Health

AI Machine Learning Scientist

Elevance Health

AI Machine Learning Scientist at Elevance Health developing scalable AI and machine learning solutions for business challenges. Collaborating with cross-functional teams to optimize AI systems and practices.

Posted 6/16/2026full-timeRichmond • Florida, Virginia • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies
CloudDistributed SystemsPythonPyTorchTensorflow

About the role

Key responsibilities & impact
  • Design, develop, and deploy AI/ML and Generative AI solutions that address business and operational challenges at enterprise scale.
  • Build and maintain infrastructure, pipelines, and services that connect structured and unstructured data sources for AI-driven applications.
  • Develop reusable AI capabilities including RAG pipelines, vector search, semantic retrieval, prompt orchestration, and agentic workflows.
  • Implement evaluation frameworks and automated testing strategies to measure model quality, accuracy, bias, safety, and performance.
  • Establish monitoring, observability, and governance processes to ensure AI systems remain reliable and compliant in production.
  • Collaborate with engineering and product teams to integrate AI capabilities into enterprise platforms and applications.
  • Drive adoption of Responsible AI practices by implementing evaluation standards, audit-ready documentation, and model governance controls.
  • Optimize AI systems for scalability, latency, reliability, and cost efficiency.
  • Support experimentation, benchmarking, and model comparison activities to improve decision-making and accelerate AI innovation.
  • Partner with cross-functional stakeholders to translate business requirements into production-ready AI capabilities and services.
  • Contribute to technical standards, architecture decisions, and best practices for enterprise AI engineering.
  • Develop experimental and analytic plans for machine learning algorithms and data modeling processes, use of strong baselines, and ability to accurately determine cause and effect relations.

Requirements

What you’ll need
  • 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.
  • Experience building and deploying LLM- or SLM-based applications in production environments highly preferred.
  • Experience developing Retrieval-Augmented Generation (RAG) systems, semantic search, vector databases, embeddings, and prompt engineering techniques highly preferred.
  • Experience designing and implementing AI agents, tool-calling workflows, or agentic architectures highly preferred.
  • Experience evaluating AI systems using automated evaluation frameworks, benchmarking approaches, and human-in-the-loop review processes highly preferred.
  • Experience building scalable AI/ML pipelines and services using cloud-native architectures highly preferred.
  • Experience with MLOps practices including CI/CD, model deployment, monitoring, observability, drift detection, and lifecycle management highly preferred.
  • Experience with Python and modern AI/ML frameworks and libraries (e.g., PyTorch, TensorFlow, LangChain, LangGraph, LlamaIndex, Hugging Face, or equivalent) highly preferred.
  • Familiarity with Responsible AI principles, model governance, bias testing, explainability, and auditability requirements highly preferred.
  • Experience integrating AI solutions with APIs, enterprise platforms, and distributed systems preferred.
  • Experience reviewing, testing, validating, and hardening AI-generated code and AI-assisted development workflows preferred.
  • Experience supporting production AI systems, troubleshooting issues, and driving continuous improvement preferred.
  • Strong communication and collaboration skills with the ability to influence technical and non-technical stakeholders preferred.
  • Healthcare, regulated industry, or enterprise-scale AI experience preferred.

Benefits

Comp & perks
  • merit increases
  • paid holidays
  • Paid Time Off
  • incentive bonus programs
  • medical, dental, vision
  • short and long term disability benefits
  • 401(k) +match
  • stock purchase plan
  • life insurance
  • wellness programs
  • financial education resources

ATS Keywords

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Hard Skills & Tools
AI solutionsML solutionsGenerative AIRAG pipelinesvector searchsemantic retrievalautomated testing strategiesMLOpsPythonAI/ML frameworks
Soft Skills
communication skillscollaboration skillsinfluence skills