Lead Data Scientist - Autonomous Goal Management
About The Position
Become a part of our caring community and help us put health first The Enterprise AI organization at Humana is a pioneering force, driving AI innovation across our Insurance and CenterWell business segments. By collaborating with world-leading experts, we are at the forefront of delivering cutting-edge AI technologies for improving care quality and experience of millions of consumers. We are actively seeking top talent to develop robust and reusable AI modules and pipelines, ensuring adherence to best practices in accountable AI for effective risk management and measurement. Join us in shaping the future of healthcare through AI excellence. We are building advanced agentic systems capable of autonomously managing and decomposing complex goals. We are seeking an expert in agent design, planning, and control to develop and evaluate agents that can set, adapt, and execute goals in dynamic, real-world environments. You’ll contribute to the scientific and engineering foundations that make AI agents reliable, interpretable, and robust across long-horizon tasks.
Requirements
- Proficiency in SQL, Python, and data analysis/data mining tools.
- Experience with machine learning frameworks like Pytorch, Jax, LangChain, LangGraph or AutoGen
- Experience with high performance, large-scale ML systems
- Experience with language modeling with transformers
- Experience with symbolic planning, causal reasoning, and model-based RL
- Experience with large-scale ETL
- Master's Degree and 4+ years of experience in research/ML engineering or an applied research scientist position preferably with a focus on developing production-ready AI solutions
- 2+ years of experience leading development of AI/ML systems
Nice To Haves
- Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
- Demonstrated experience shipping autonomous, or semi-autonomous agents in production or simulation
- Experience with LLM-based agents with scratchpad/self-reflection or hierarchical task decomposition
- Understanding of autonomy risk mitigation strategies, including off-switch protocols, or bounded rationality
Responsibilities
- Architect goal setting and goal decomposition mechanisms for autonomous agents operating in uncertain or open-ended environments
- Design and implement dynamic planning systems (e.g., hierarchical planning, curriculum learning, scratchpad/self-refinement loops)
- Collaborate on memory, tool-use, and feedback-loop designs enabling multi-step, self-directed agent behavior
- Develop evaluation frameworks for alignment with human intent, consistency, progress against long-horizon objectives
- Prototype agents that interface with APIs, MCP servers, search engines, databases, or real-world actuators to pursue goals safely and efficiency
- Explore mechanisms to detect and mitigate goal misalignment, looping behavior, or undesirable emergent strategies
- Work across teams to integrate goal alignment with safety, alignment, and operational reliability mechanisms
Benefits
- Work-Life Balance
- Generous PTO package
- Health benefits effective day 1
- Annual Incentive Plan
- 401K - Excellent company match
- Well-being program
- Paid Volunteer Time Off
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
