We are seeking a hands-on research lead to guide our efforts in reinforcement learning and post-training for agentic AI. This role involves managing a small team of senior researchers and shaping the direction of research in areas such as synthetic environment generation and multimodal action models. The team focuses on developing infrastructure and evaluation procedures for interactive agents, aiming for impactful research that aligns with Apple's deployment realities. The position emphasizes continued engagement with the academic community and hands-on involvement in research.

• PhD in machine learning or a related field, or equivalent research experience
• 7-10+ years of research experience beyond PhD in industry or as an academic research lead
• Strong track record in reinforcement learning and/or post-training of large models, demonstrated through publications or open-source contributions
• Leadership experience in setting and defending a research direction and directing others' work
• Experience owning ML infrastructure, frameworks, and codebases
• Strong engineering skills and comfort working hands-on in large training codebases
• Experience taking research from idea to product or production impact
• Familiarity with efficiency-aware modeling techniques
• Interest or background in open-endedness, evolutionary computation, or self-improving systems
• Principled or theoretical grounding in reinforcement learning
• Breadth across core machine learning areas and perspective on the field's longer arcs
• Experience growing and managing researchers and engineers with heterogeneous specialties
• Experience owning a large reinforcement learning or post-training codebase

• Lead research on reinforcement learning and post-training for agentic capabilities.
• Build and own synthetic data and task-generation pipelines.
• Drive codebases and infrastructure for the core reinforcement learning research effort.
• Manage and mentor a small team of senior researchers and research engineers.
• Stay hands-on by running experiments, writing code, and contributing to technical problems.
• Connect post-training research to efficiency and deployment considerations.
• Collaborate across the organization on methods for environment and agent co-optimization.
• Publish in top venues and engage with the broader research community.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.