Agentic AI/ML Engineer Intern, Solutions

FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market. Why Join FieldAI in Irvine? In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use. You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments. Be Part of the Next Robotics Revolution We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world. Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like. We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected statu What You'll Do Design and implement agentic workflows with tool use, memory, and orchestration to automate repetitive tasks and answer questions over internal and customer-facing data. Contribute to AI Ops (agent infrastructure) — orchestration, evals, and observability — and apply it to enable agent-native DevOps that automates our engineering and internal operations workflows. Build and optimize RAG pipelines with vector DBs and knowledge graphs to ground agents in the right context. Set up evaluation pipelines to measure agent quality, reliability, and performance. What You Bring Educational Track: Currently pursuing a BS, MS, or Ph.D. in Computer Science, AI/ML, Robotics, or a related technical field, with deep project-based experience. Strong evidence of building agentic projects (hackathons, research, internships, or personal projects). Agentic & ML Foundation: Solid theoretical understanding and practical application of Agentic Engineering principles (Tool Use, Memory, RAG, Planning). Production-Grade Python: Proven ability to write reliable, testable, clean, and performant Python code, with familiarity with software engineering best practices, including version control, containerization (Docker), and test-driven development (pytest). Advanced Agent Orchestration: Hands-on engineering experience with modern, open-source agentic frameworks (e.g., LangChain, LangGraph, LlamaIndex) rather than relying strictly on service-managed agent APIs. AI Ops & Observability: Experience implementing evaluation, tracing, and monitoring pipelines (e.g., MLflow, Langfuse, TruLens) to quantitatively measure agent quality, factual accuracy, latency, and reliability. Information Retrieval & Grounding: Practical expertise building and optimizing context-aware systems, with hands-on experience using Vector Databases (e.g., Pinecone, FAISS, OpenSearch) and designing Knowledge Graphs to reliably ground agents and mitigate hallucinations. Cloud / Robot Compute: Familiarity with Cloud Platforms (e.g., AWS, GCP) for ML/AI deployment, and/or experience with on-robot compute environments. Bias for action and ownership : Ability to take a loosely defined, complex problem and define and drive a working solution end-to-end. Strong ability to drive solutions end-to-end , including cross-team coordination and seeking out customer input to shape what gets built. Strong communication, initiative, and ability to learn quickly in a fast-moving team. What Sets You Apart Deep experience designing and operating AI Ops infrastructure at production scale, including robotics-grade data logging and observability (e.g., Foxglove). Experience with advanced agent patterns: Multi-Agent Systems , Human-in-the-Loop workflows , or Long-Horizon Planning . Prior experience shipping internal tools or customer-facing assistants used by real users. Personal projects and a portfolio of agentic builds are a big bonus — we love seeing what you’ve shipped on your own.

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