Machine Learning Engineer, LLMs, Agent Systems, and Simulation Tooling, Siri Core Modeling

What you'll do

• Design and implement scalable simulation and evaluation frameworks for LLM-based agents.
• Translate novel reasoning approaches from research into production-grade systems.
• Develop infrastructure for training and experimentation with agentic behaviors.
• Integrate agent reasoning capabilities into client-side and backend environments.
• Create reliable tooling for experimentation, prototyping, and deployment to drive iteration speed.
• Design and run experiments in simulated environments to evaluate agent actions.
• Build scalable evaluation pipelines for agentic LLMs.

What we're looking for

• Bachelor’s degree in Computer Science, Machine Learning, or a related quantitative field.
• 3+ years of relevant industry experience.
• Strong skills in Python (preferred) and at least one other programming language.
• Proven experience in ML engineering, including system design, training pipelines, and deployment workflows.
• Deep understanding of agent-based simulation, agentic RAG systems, and LLM evaluation methodologies.
• Experience deploying LLM models in research or production contexts (preferred).
• Knowledge of adaptive feedback loops, reinforcement learning, or interactive agent design (preferred).
• MS or PhD in Computer Science, Machine Learning, or a related field (preferred).