About the job
The System Intelligence and Machine Learning (SIML) Content Understanding teams are seeking a Research Engineer 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.
Responsibilities
fluency in algorithm development (prompt optimization, post training / alignment), and experience with automatic evaluation techniques. 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
testing and upkeep of training infrastructure, whiled partnering with safety/security teams on emerging robustness challenges while aligning models/agents to production needs. Ability to interface with large scale data infrastructure is a huge plus.
Qualifications
Minimum
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
Proven experience in one of the following: Reinforcement Learning, Multimodal Training, Pre-training / Post-training foundation models
Proficiency in using ML toolkits, e.g., PyTorch
Track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm
Preferred
Experience with building & deploying Multimodal-LLMs
Familiarity with distributed training and large-scale data infrastructure