FieldAI
Product Engineering
AgenticAI/MLEngineer
Neural analysis suggests this role is
optimal for Entry candidates.
“Agentic AI/ML Engineer at FieldAI. Skills: Agentic AI, AI Ops, RAG, Robotics. Design agentic workflows. Leverage tool use”
What You'll Achieve.
Improve system performance; Deliver actionable insights
Industry & Context.
Break down ambiguous problems; Troubleshooting
What They're Looking For.
Must Have
BS, MS, or Ph. D. in CS, AI, ML, Robotics, or related field, or equivalent experience, Python engineering skills, Familiarity with software engineering best practices, Hands-on experience with modern agent frameworks, Experience building, evaluating, and improving AI systems, Familiarity with retrieval and grounding techniques, Experience working with cloud platforms
Nice to Have
Robotics, edge computing, or on-device AI systems experience is a plus, Experience building, operating, or contributing to AI infrastructure, Familiarity with advanced agentic patterns, Experience building AI-powered products, Exposure to robotics, autonomy, edge computing, or large-scale operational systems, Familiarity with observability and debugging tools for AI and robotic systems, Contributions to open-source projects, Portfolio of personal projects
What You'll Do.
Design agentic workflows
Leverage orchestration
Automate repetitive tasks
Enable natural-language access
Contribute to AI Ops platform
Develop agent infrastructure
Apply capabilities to agent-native DevOps workflows
Automate engineering processes
Automate support processes
Automate operational processes
Develop retrieval systems
Optimize retrieval systems
Provide agents with context
Build evaluation frameworks
Build automated testing pipelines
Measure agent quality
Measure agent reliability
Measure agent latency
Measure business impact
Improve system performance
Prototype AI-powered tools
Iterate AI-powered tools
Deploy AI-powered tools
Improve internal productivity
Deliver actionable insights
Partner with engineering teams
Partner with product teams
Partner with field operations teams
Partner with customer-facing teams
Identify high-leverage opportunities
How You'll Work.
Team & Collaboration
Cross-functional teams; Engineering teams; Product teams; Field operations teams; Customer-facing teams
Full Job Description
## Description 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. ## What You Do 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. ## What You Bring BS, MS, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related technic
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