4 hours ago
Responsibilities
- Contribute to model development and fine-tuning workflows for generative AI features.
- Design and evaluate retrieval strategies for grounding large models in product-relevant data.
- Prototype and benchmark multi-agent collaboration systems for structured reasoning tasks.
- Build multi-turn, conversational, agentic applications and frameworks for Apple customer support.
- Enhance a multimodal, multi-agent platform with a focus on latency, cost, and customer experience.
- Partner with data and platform engineers to support scalable deployment and monitoring.
- Deploy systems to cloud environments including AWS, GCP, or on-remote hybrid environments.
Requirements
- 4+ years of hands-on experience in machine learning, backend engineering, or data engineering.
- At least 1 year of hands-on experience training, fine-tuning, or evaluating large language models.
- Proficiency with machine learning libraries including transformers and datasets.
- Bachelor’s or master’s degree in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
- Foundational understanding of retrieval-augmented generation architectures and vector-based retrieval systems.
- Strong problem-solving and collaboration skills with the ability to learn quickly and adapt to production-grade systems.
- Experience deploying to cloud environments is required.
- Experience with multimodal large language models for voice capabilities, or prior experience with speech-to-text or text-to-speech systems, is preferred.
Tech Stack
Categories
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.