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

Join Apple’s Siri organization in Cupertino, CA (onsite) to help define how next-generation intelligent agents reason, plan, and interact through natural voice and multimodal experiences. In this senior Machine Learning Engineering role, you will build scalable LLM reasoning systems and the simulation and evaluation tooling that supports agentic voice capabilities across client and backend environments.

What you’ll do

• Design and implement scalable simulation and evaluation frameworks for LLM-based agents.
• Develop infrastructure for training and experimentation with agentic behaviors, including how agents plan, adapt, and evaluate actions in realistic environments.
• Build scalable evaluation pipelines and create reliable tooling to accelerate iteration for prototyping and deployment.
• Integrate agent reasoning capabilities across client-side and backend environments.
• Collaborate with ML researchers and applied researchers to translate novel reasoning approaches into production-grade systems.
• Run experiments in simulated environments to advance robust, trustworthy agent behavior.

What you bring

• Experience deploying LLM models in research or production contexts.
• Knowledge of adaptive feedback loops, reinforcement learning, or interactive agent design.
• Familiarity with client-backend integration for AI-driven applications.
• Strong Python skills (preferred) and proficiency in at least one other programming language.
• Proven ML engineering background, including system design, training pipelines, and deployment workflows.
• Deep understanding of agent-based simulation, agentic RAG systems, and LLM evaluation methodologies.
• Ability to balance long-term platform vision with pragmatic short-term delivery in fast-paced environments.
• Minimum education/experience: Bachelor’s degree in Computer Science, Machine Learning, or a related quantitative field, plus 3+ years of relevant industry experience.
• Advanced degree preferred: MS or PhD in Computer Science, Machine Learning, or a related field.

Technologies you’ll work with

• Python
• Reinforcement learning
• Agentic RAG systems
• LLM evaluation methodologies

Pay & benefits

Base pay range: USD 150,400 - 277,600 per year, determined based on skills, qualifications, experience, and location.

• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
• Eligible for discretionary restricted stock unit awards
• Can purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan
• Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation

Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.