Internship Docker Developer Jobs in Riverside, CA

Job Summary:
FieldAI is a company based in Irvine, California, focused on building reliable AI systems for robotics. The Agentic AI/ML Engineer will design workflows, develop AI infrastructure, and optimize systems to enhance automation and performance in real-world deployments.
Responsibilities:
• Design and build agentic workflows that leverage tool use, memory, planning, and orchestration to automate repetitive tasks and enable natural-language access to internal and customer-facing data.
• Contribute to FieldAI's AI Ops platform by developing agent infrastructure for orchestration, evaluation, observability, and reliability. Apply these capabilities to create agent-native DevOps workflows that automate engineering, support, and operational processes.
• Develop and optimize retrieval systems, including RAG pipelines, vector databases, and knowledge graph integrations, to provide agents with accurate, relevant, and scalable context.
• Build evaluation frameworks and automated testing pipelines to measure agent quality, reliability, safety, latency, and business impact, and use those insights to continuously improve system performance.
• Prototype, iterate, and deploy AI-powered tools that improve internal productivity and deliver actionable insights to customers.
• Partner closely with engineering, product, field operations, and customer-facing teams to identify high-leverage opportunities for automation and agent-driven workflows.
Qualifications:
Required:
• BS, MS, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related technical field, or equivalent hands-on experience. Recent graduates and candidates with up to approximately one year of professional experience are encouraged to apply.
• Strong evidence of building and shipping AI or agentic systems through academic research, internships, hackathons, open-source contributions, or personal projects.
• Solid understanding of modern agentic AI concepts, including tool use, memory, retrieval-augmented generation (RAG), planning, and multi-step reasoning, with experience applying these concepts in real-world projects.
• Strong Python engineering skills, including writing clean, maintainable, testable, and performant code. Familiarity with software engineering best practices such as version control, containerization (Docker), CI/CD, and automated testing.
• Hands-on experience with modern agent frameworks and orchestration systems such as LangGraph, LangChain, LlamaIndex, CrewAI, or similar technologies.
• Experience building, evaluating, and improving AI systems through structured testing, benchmarking, observability, tracing, and monitoring frameworks.
• Familiarity with retrieval and grounding techniques, including vector databases, semantic search, knowledge graphs, and other approaches used to improve agent accuracy and reliability.
• Experience working with cloud platforms such as AWS, GCP, or Azure for deploying and operating AI/ML systems. Experience with robotics, edge computing, or on-device AI systems is a plus.
• Demonstrated ownership and bias for action, with the ability to take an ambiguous problem, break it down into actionable steps, and deliver working solutions.
• Strong collaboration and communication skills, including the ability to work across engineering, product, operations, and customer-facing teams to understand requirements and drive outcomes.
• Curiosity, initiative, and a desire to learn quickly while contributing in a fast-paced, high-growth environment.
Preferred:
• Experience building, operating, or contributing to AI infrastructure, evaluation systems, observability platforms, or data pipelines that support production AI applications.
• Familiarity with advanced agentic patterns such as multi-agent systems, human-in-the-loop workflows, long-horizon planning, tool orchestration, or autonomous task execution.
• Experience building AI-powered products, internal developer tools, copilots, assistants, or workflow automation systems used by real users.
• Exposure to robotics, autonomy, edge computing, or large-scale operational systems.
• Familiarity with observability and debugging tools for AI and robotic systems, such as Langfuse, MLflow, Weights & Biases, Foxglove, or similar platforms.
• Contributions to open-source projects, research publications, technical blogs, competition results, or other publicly available work that demonstrates technical depth and initiative.
• A portfolio of personal projects, hackathon submissions, or agentic applications you've designed and shipped independently. We love seeing what you've built.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.