Senior Machine Learning Engineer, Apple Search & Knowledge Platforms

Apple
Seattle, United States of America2026-01-14

About the job

In this role, you will work on LLM based question answering and Apple Intelligence features to provide concise, accurate, and grounded information to users to help them complete their tasks quickly on Apple devices. The AI, Search & Knowledge Platforms team builds amazing products and services for Apple's customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI, search, and knowledge systems powering Siri, Apple Intelligence, Safari, and iMessage, and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale.

Responsibilities

Designing and developing advanced Reinforcement Learning technologies in the post-training of generative model, and delivering the end-user experience.

Driving cross-functional technical initiatives, collaborating with research, engineering and production teams to translate theoretical advances into deployable systems.

Developing novel and cutting-edge RL algorithms and improving existing ones.

Staying up to date with the latest RL research and integrate best practices into the team's workflow.

Working on the end-to-end ML lifecycle: algorithm design and implementation, data collection, model training, evaluation, and deployment.

Qualifications

Minimum

3+ years of ML experiences in search, natural language processing/understanding. Conversational AI.

Proven experience for LLM post training, including but not limited to SFT, RLHF, RLAIF, Reward Modeling, Chain-of-thought, agentic LLM.

Hands-on experience building RL pipelines and training agents in simulation or real-world environments.

Growth mindset and ability to learn new technologies

MS or Ph.D. in Computer Science, Machine Learning with a specialty in reinforcement learning, or a related field

Preferred

Deep expertise in reinforcement learning-based post-training on LLM models, reward modeling, RLHF, RLAIF, Chain-of-thought, and agentic AI R&D.

Deep understanding of cutting edge RL algorithms and large language model.

Deep understanding in LLM pre-training, post-training.

Strong product intuition and ownership

Excellent communication skills