Research Engineer, Reasoning & Memory - SIML
Apple
Cupertino, CA, USA
USD 147,400-272,100 / year + Equity
Posted on Apr 9, 2026
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. 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/
Important attributes expected in the role is 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 Other responsibilities include 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. Apple has a thriving Machine Learning research community. It is expected that role offers the candidate an opportunity to form a strong network of collaborators across the company, while sharing research progress with senior technical leaders at a regular cadence.
- 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
- Experience with building & deploying Multimodal-LLMs
- Familiarity with distributed training and large-scale data infrastructure
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.