Sr Research Manager, Multimodal Reasoning SIML

The System Intelligence and Machine Learning (SIML) Content Understanding team is seeking a Senior Research Manager in Multimodal Reasoning. You will be working alonside teams that are in charge of operating system wide embeddings personalized RAG workstreams tool calling context compaction / efficiency u0026 memory systems. Projects are focussed on advancing Apple Intelligence capabilities while working closely across disciplines with our partners in hardware engineering design and product. nnSelected references to our prior work:n(a) are seeking a senior applied research leader in multimodal reasoning. The role expects fluency in algorithm development and computation ability to set up future facing research investigations and leading cross functional teams on company wide efforts. Key attributes expected in the role is fluency with state of art LLM workflows (prompt optimization post training / alignment automatic evaluation distributed training u0026 inference). nnThe role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences. Ability to interface with large scale modeling u0026 data infrastructure is a huge plus.

PhD or MSc in Computer Science/Electrical Engineering or a related field (mathematics physics or computer engineering); with a focus on machine learning or comparable professional experiencenStrong ML and Generative Modeling fundamentalsn3 years of experience leading and growing high-performing machine learning teams of individual expertise in one of the following: Reinforcement Learning Multimodal Training Pre-training / Post-training foundation models nProficiency in using ML toolkits e.g. PyTorchnProven track record of research contributions demonstrated through publications in top-tier conferences or open source contributions to algorithm

Experienced in leading applied research efforts in Multimodal-LLMsnTrack Record in transitioning applied research initiatives to customer facing experiencesnFamiliarity with distributed training and large-scale data infrastructure