AIML - Machine Learning Research

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. Your core responsibilities will include: * 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. Minimum Qualifications 1+ 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. Experienced researcher in areas of machine learning, including natural language or speech 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 Qualifications Deep expertise in reinforcement learning-based post-training on LLM models, reward modeling, RLHF, RLAIF, Chain-of-thought, and agentic AI R&D. Experienced researcher with publications in areas of machine learning, including natural language processing 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