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

Machine Learning, Generative Modeling, Reinforcement Learning, Multimodal Training, PyTorch, Algorithm Development, Prompt Optimization, Post-training, Alignment, Automatic Evaluation, Distributed Training, Large-scale Data Infrastructure, Reasoning Systems, Memory Systems, Agentic Experiences

Industry

Computers and Electronics Manufacturing

Description

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/ DESCRIPTION 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. 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 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 QUALIFICATIONS Experience with building & deploying Multimodal-LLMs Familiarity with distributed training and large-scale data infrastructure

Responsibilities

You will develop and implement reasoning and memory systems to advance Apple Intelligence capabilities. This involves partnering with cross-functional teams to prototype algorithmic innovations and maintain training infrastructure.