AI Tooling & Analytics Intern
Location: San Francisco, CA
Department: Engineering
Nimble is an AI robotics company building the autonomous supply chain to power fast, efficient and economical commerce. We’re training robot AGI to power a proprietary generalist supply chain superhumanoid, the first robot in the world capable of performing thousands of tasks across the supply chain. We’ve raised over $220M at over $1B valuation and formed a strategic alliance with FedEx to build a national network of autonomous warehouses capable of generating many billions in annual revenue. We are a hardcore and obsessed team of the world’s best engineers and operators. If you are obsessed with your craft, enjoy a high-intensity and fast moving high impact environment, are super high agency in getting hard things done and want to be part of building the world’s most legendary robotics company at the most pivotal moment in history, we want to work with you.
We are on a mission to empower and inspire mankind to accomplish legendary feats by inventing robots that liberate us from the menial. We will accomplish this by training robot AGI to invent and build the Autonomous Supply Chain – everything from the inside of factories and warehouses to your front door – powered by generalist superhumanoids.
Our founding team comes from the AI labs at Stanford and Carnegie Mellon and our board of directors include famed robotics and AI legends including Fei-Fei Li (Chief Scientist of AI at Google and Director of Stanford’s AI Lab), Marc Raibert (founder of Boston Dynamics), and Sebastian Thrun (founder of GoogleX, Waymo; Stanford Professor and considered the father of autonomous vehicles).
Let’s be legendary.
The Role
The Robot Analytics team is seeking a technically-driven intern to develop our Internal AI Agent. This assistant provides our Engineering and Operations teams with real-time visibility, automated troubleshooting, and streamlined workflows across our scaled robotic fulfillment centers. You will build the agentic infrastructure and Model Context Protocols (MCP) to connect LLMs with robot telemetry, databases, and system logs. Your goal is to bridge the gap between complex production data and actionable operational insights through a mix of AI automation and deep data analysis.
Responsibilities
Build Agentic Tooling: Design and implement MCP servers that enable the AI assistant to interface with real-time robot data and internal APIs
Analytical Infrastructure: Query and analyze large-scale datasets to identify performance trends, fleet health metrics, and edge-case failure modes.
Automate Workflows: Identify manual engineering support and operational tasks and translate them into autonomous, multi-step agentic routines
Enhance Visibility: Develop retrieval strategies (RAG) and tool-calling capabilities to allow teams to query production health using natural language
Iterative Development: Collaborate with Engineering and Ops to identify data gaps and refine the agent’s reasoning accuracy
Qualifications
- Education: Pursuing a degree in CS, Robotics, Mechatronics, or a related engineering field
- Technical Skills: Strong proficiency in Python and SQL; comfortable in Linux environments
- Data Fluency: Experience performing root-cause analysis and extracting insights from high-dimensional system telemetry and logs
- AI Interest: Familiarity with LLM orchestration and MCP architectures
Compensation
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