ML & Agentic Systems Engineer [IC4]
Core
Building the infrastructure for agentic development by designing multi-step agent loops, managing model selection and fine-tuning, and engineering retrieval systems to provide context for AI tools navigating massive codebases.
Role type
Staff Machine Learning and Agent Systems Engineer (Technical Leader)
Builds
Production agentic systems, model evaluation pipelines, and code understanding features for engineering teams and AI agents
Domain
Software Engineering / Artificial Intelligence / Large Language Models
Deliverable
production ML models | product features | infrastructure
Required skills
Production ML lifecycle ownership, multi-step agent system design, model evaluation strategy, retrieval and context engineering, model fine-tuning and distillation, cost and latency optimization
Preferred skills
Experience with enterprise-scale codebases, leading technical direction for AI products, mentoring teams in agent engineering
Technologies
LLMs, agentic frameworks, evaluation harnesses, retrieval systems, fine-tuning pipelines
Responsibilities
Design and harden multi-step, tool-using agent loops; craft evaluation strategies to measure product impact; select, upgrade, and fine-tune models; engineer retrieval and context grounding; optimize cost and latency as product features; set technical standards and mentor the team
Seniority
Staff, technical leader with strategic direction and mentorship
