AIML Intern en Barcelona

The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries! It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Apple’s Services - App Store, iCloud, Apple Music, TV+, and many more - are the most exciting and dynamic in the world. Our teams work together to craft products and experiences that impact people’s lives in ways they could not have imagined. We are looking for an exceptional candidate to design and implement solutions for knowledge and GenAI for our Services. If you are interested in driving a critical and growing part of creating top tier experiences this role may be for you!

Description

As a member of our dynamic and fast-paced group, you’ll work in different research areas to take new knowledge, NLP and GenAI algorithms/models from prototype to production while coordinating with different teams and stakeholders. In this role you will combine knowledge, language and generative algorithms/models that enable high-quality user experiences for different use cases and applications. All of this while delivering high-quality production code and working with cutting-edge technology. You must be comfortable working with industry-scale graphs, state-of-the-art NLP and generative models, and doing research for quickly building competence and bring insights into your work. The ideal candidate will have experience at the intersection between knowledge graphs and GenAI technologies, explainable AI, machine learning lifecycle management, coupled with strong fundamentals and passion in software engineering.

Minimum Qualifications

• Interest in combining Knowledge Graphs and GenAI to build explainable ML solutions
• Solid ML and NLP foundation
• Strong software engineering skills
• Avid learner, and comfortable working in cross-functional teams
• Familiarity with research papers, implementing state-of-the-art methods, and adapting them to practical applications

Preferred Qualifications

• Hands-on experience working with distributed systems (ie, Spark, Kafka, Kubernetes)
• Experience with Knowledge Graph technologies (SPARQL, Gremlin, Graph DBs)
• Experience with Knowledge Graph ML (ie, graph traversal algorithms, kGNNs, GraphRAG)
• Caught up with state-of-the-art Knowledge Representation, and Information Extraction
• Strong mathematical skills in linear algebra and statistics.