Data Scientist, Principal - AI Product Engineering
About The Position
The Data Scientist, Principal will lead development and deployment of novel applications leveraging generative AI models, set technical direction for AI and machine learning across the organization, and translate cutting-edge research into production products. The role focuses on rapidly developing new features and partnering across teams to maximize impact, taking products and features from 0 to 1. Products include LLM-powered applications, AI agents and copilots, retrieval-augmented generation (RAG) and search, and AI-enabled automation embedded in customer-facing applications and enterprise workflows, including claims, payment integrity, clinical insights, and member experience. The position works with researchers and product managers to build scalable applications, APIs, services, and data and retrieval pipelines; evaluates and improves model performance; and optimizes reliability and performance of deployed applications. It also champions generative AI development and deployment best practices and mentors team members in a collaborative, high-performing environment. The role is part of the AI & Machine Learning team, which partners across the enterprise to apply AI, machine learning, and generative AI to build intelligent products. It reports to the Director, AI & Machine Learning. The position follows a hybrid workplace model, generally requiring office attendance two days per week, with in-office schedules subject to business needs and individual circumstances.
Requirements
- Bachelor’s degree in computer science, a quantitative discipline, or equivalent practical experience.
- 10 years of prior relevant experience in data science, machine learning, applied AI/ML, software engineering, or advanced analytics.
- Proven track record of rapidly building and shipping software products, not only models or analyses.
- Strong software engineering skills and proficiency in Python, including building APIs and backend services.
- Experience leading ML design and optimizing ML infrastructure, model deployment, evaluation, and data processing, and working with machine learning frameworks and libraries.
- Hands-on experience with deep learning and LLM application frameworks, including PyTorch, TensorFlow, LangChain, and LangGraph.
- Hands-on experience building applications that leverage generative AI models, including prompt engineering and RAG.
Nice To Haves
- Master’s degree or PhD; advanced degrees in a relevant field may be considered in lieu of a portion of the required experience.
- Experience with generative AI research or applications.
- Experience designing agent-based systems and orchestration frameworks.
- Experience with cloud computing platforms and infrastructure such as Azure, Google Cloud, or AWS, and scalable data processing with SQL or Spark.
- Solid MLOps and LLMOps practices, including CI/CD, monitoring, and model lifecycle management.
- Experience rapidly developing and shipping software in a fast-paced, customer-facing environment while adapting to changing priorities.
- Understanding of responsible AI and governance for regulated or healthcare environments.
Responsibilities
- Lead development and deployment of novel applications that leverage generative AI models and set technical direction for AI and machine learning across the organization.
- Design and develop scalable generative AI applications, including LLM applications, copilots, agents, RAG, and search, embedded in customer-facing products and enterprise workflows.
- Rapidly prototype new features and iterate based on evaluation results.
- Lead architecture and development of new products and features from 0 to 1.
- Collaborate with researchers and product managers to translate AI research into product features.
- Build APIs, services, and data and retrieval pipelines that expose AI capabilities to applications.
- Optimize software performance and ensure deployed application reliability.
- Champion best practices for building and deploying generative AI applications.
- Evaluate model performance, analyze results, and implement improvements while ensuring responsible and compliant AI.
- Mentor and develop team members and foster a collaborative, high-performing environment.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
