Agent Sciences and Infrastructure Engineer, AIML

What you'll do

• Build and operate infrastructure for machine learning training, evaluation pipelines, and data tooling.
• Develop agentic systems and frameworks to prototype and ship Apple Intelligence features.
• Design and maintain distributed systems, APIs, and reliable code for large language models.
• Create tools for LLM evaluation, tool-use systems, and post-training optimization workflows.
• Manage data standardization, validation, and lineage for machine learning pipelines at scale.
• Identify performance bottlenecks in research and translate them into robust production tooling.
• Lead complex, multi-month engineering projects from ambiguous starting points to production.
• Implement benchmarking and observability practices for complex AI systems.

What we're looking for

• Ability to independently scope and lead complex, multi-month engineering projects from ambiguous starting points to production.
• Experience designing, building, and operating infrastructure for machine learning training, evaluation pipelines, data tooling, or agent harnesses.
• Strong software engineering fundamentals in distributed systems, APIs, testing, and writing reliable code.
• Proficiency in Python and UNIX environments including the use of agentic coding tools.
• Experience with LLM evaluation infrastructure, tool-use systems, or agent frameworks.
• Familiarity with post-training, optimizing large language models, and associated workflows.
• Ability to identify bottlenecks in research and translate them into robust tooling.
• A BS with 5+ years experience, an MS with 3+ years experience, or a PhD with 1+ year experience.