Lead RL Researcher for Agentic AI & Environments

Apple Inc.; Cupertino, Northern (CA, KY); Hybrid; USD 216,000 - 394,000; Full time

Benefits offered by this job

Apple stock programs

Medical coverage

Retirement benefits

Tuition reimbursement

Job summary

Apple Inc. in Cupertino, CA is seeking a hands-on research lead to drive reinforcement learning and post-training work for agentic AI, and to manage a small team of senior researchers in RL, agentic tool-calling, synthetic data generation, and multimodal action models.

You will help set direction for infrastructure, training, runtime and evaluation for interactive agents and on-device/hybrid deployment. The role combines research leadership with hands-on coding and experimentation, publishing in

Qualifications

• 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 RL and/or post-training of large models, demonstrated through publications, open-source contributions, or shipped systems.
• Leadership experience: setting and defending a research direction over multiple years, and directing others' work — through direct reports, PhD students, postdocs, or sustained project teams.
• Experience owning ML infrastructure, frameworks and codebases, including open-source research frameworks or environment suites others build on.

Responsibilities

• Lead research on RL and post-training for agentic capabilities: reward, preference optimization, and verifier design, training recipes, and evaluation for tool calling, coding, and multi-step interactive tasks.
• Build and own synthetic data and task-generation pipelines — generating diverse, verifiable tasks and environments, along with the interactive environments and benchmarks that go with them, and the curricula that turn them into capable agents.
• Drive codebases and infrastructure for the core RL research effort and help engage partner teams to use and co-develop the framework.
• Manage and mentor a small team (3–4) of senior researchers and research engineers with distinct specialties, shaping a shared research direction while protecting room for bottom-up, idea-driven work.
• Stay hands-on: run experiments, write code, and contribute directly to the team's most important technical problems.
• Connect post-training research to efficiency and deployment: what works under on-device and hybrid compute constraints, and how method design interacts with hardware.
• Collaborate across the organization on adjacent directions, including methods for environment and agent co-optimization, self-improvement, world models used as planners or policies, and personalized long-context agents.
• Publish in top venues and engage with the broader research community.

Skills

Reinforcement Learning

Post-training methods

Leadership

ML infrastructure

Education

PhD in ML or related field

Tools

TensorFlow

PyTorch

JAX

OpenAI Gym

Job description

Apple Inc. in Cupertino, CA is seeking a hands-on research lead to drive reinforcement learning and post-training work for agentic AI, and to manage a small team of senior researchers in RL, agentic tool-calling, synthetic data generation, and multimodal action models.

You will help set direction for infrastructure, training, runtime and evaluation for interactive agents and on-device/hybrid deployment. The role combines research leadership with hands-on coding and experimentation, publishing in