Data Scientist - Agentic AI Systems - IFS Loops Palo Alto, California, United States Research a[...]

Data Scientist - Agentic AI Systems - IFS Loops Full‑time. We are seeking a Data Scientist with a strong research mindset to help shape the future of agentic AI systems. This role blends deep analytical thinking with fast‑paced experimentation and model development, where your insights will directly inform how AI agents reason, plan, and act in dynamic environments. You’ll work on a cross‑functional team exploring how AI agents learn from real‑world data, adapt to user intent, and interact autonomously—or collaboratively—with users and systems. If you’re a self‑starter who thrives on ambiguity, builds fast, and can bridge theory with practical outcomes, this role is for you. Key Responsibilities Design and run applied research initiatives that inform the behavior and learning loops of AI agents. Build and evaluate models for planning, memory, retrieval, reasoning, or tool use in agentic systems. Develop internal tools and pipelines to test agent behavior across different environments. Analyze structured and unstructured data from user‑agent interactions, logs, and experiments. Rapidly prototype and test hypotheses to improve agent performance and reliability. Collaborate with engineering, product, and design to translate insights into deployable features. Communicate findings clearly and concisely to both technical and non‑technical audiences. Minimum Qualifications Masters or PhD in Computer Science, Applied Math, Statistics, or a related quantitative field. 4+ years of experience in data science, applied ML, or AI research. Strong Python and SQL skills; experience with libraries like scikit‑learn, PyTorch, LangChain, or any similar agentic framework. Familiarity with LLMs, retrieval‑augmented generation (RAG), reinforcement learning, and fine‑tuning. Comfort with ambiguity, fast iteration cycles, and self‑directed research. Excellent communication and storytelling skills—you can explain complex models to others clearly. Preferred Qualifications Experience working with agent frameworks (AutoGen, OpenAgents, LangGraph, etc.). Background in decision‑making models, memory systems, or multi‑agent coordination. Exposure to vector databases, embeddings, and custom RAG pipelines. Experience building evaluation frameworks or simulators for agent performance. Experience with LLM post‑training—SFT, DPO, RLHF, GRPO. Who You Are Curious—you explore the edges of what’s possible with AI agents. Action‑biased—you ship prototypes quickly and iterate based on evidence. Scientific—you bring structure to messy problems and back claims with data. Independent—you operate autonomously and drive projects end‑to‑end. Collaborative—you thrive in cross‑functional teams and open discussion. What We’re Offering Salary Range: $140,000 to $150,000 annually + bonus. Flexible paid time off, including sick and holiday. 401(k) with company contribution. Flexible spending accounts. Life insurance and disability benefits. Tuition assistance. Community involvement and volunteering events. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. VEVRAA Federal Contractor, Equal Opportunity Employer. #J-18808-Ljbffr