Staff Generative AI Research Engineer, Reasoning & Memory - SIML at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

08 Jul, 26

Salary

0.0

Posted On

09 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Reasoning, Memory Systems, Algorithm Development, Prompt Optimization, Post-training, Reinforcement Learning, Multimodal Reasoning, Agentic Workflows, PyTorch, Machine Learning, Distributed Training, Large-scale Data Infrastructure, Foundation Models, System Engineering

Industry

Computers and Electronics Manufacturing

Description

The System Intelligence and Machine Learning (SIML) Content Understanding teams are seeking a Staff Applied Researcher in Reasoning & Memory Systems. You will be working alonside teams that are in charge of operating system wide embeddings, personalized RAG workstreams, tool calling, context compaction / efficiency & memory systems. Projects are focussed on advancing Apple Intelligence capabilities, while working closely across disciplines with our partners in hardware engineering, design and product. Selected references to our prior work (a) https://arxiv.org/pdf/2507.13575, (b) https://arxiv.org/pdf/2407.21075, (c) https://www.apple.com/newsroom/2024/12/apple-intelligence-now-features-image-playground-genmoji-and-more/ DESCRIPTION We are seeking a candidate with a track record in algorithm development for agentic reasoning & memory. Key attributes expected in the role are fluency in algorithm development (prompt optimization and post training), strong expertise with relevant techniques (reinforcement learning, multimodal reasoning), and experience with automatic evaluation approaches for agentic workflow. The 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 & data infrastructure is desired. MINIMUM QUALIFICATIONS 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 experience Strong ML and Generative Modeling fundamentals Strong expertise in one of the following: Reinforcement Learning, Multimodal Training, Pre-training / Post-training foundation models Proficiency in using ML toolkits, e.g., PyTorch Proven track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm PREFERRED QUALIFICATIONS Experience with building & deploying Multimodal-LLMs Familiarity with distributed training and large-scale data infrastructure

Responsibilities

You will develop and prototype advanced algorithms for agentic reasoning and memory systems to enhance Apple Intelligence capabilities. The role involves collaborating with cross-functional teams in hardware, design, and product to integrate cutting-edge innovations into system-wide experiences.