Remote Tokenization Jobs in Texas (NOW HIRING)

At Apple, we are driven to deliver exceptional experiences through ultra-fast, thoughtfully designed, and meticulously crafted solutions. Our team is not just any group; we are a highly motivated, fast-paced, and dynamic collective of professionals committed to scaling new heights and achieving excellence. We seek individuals who strive beyond mediocrity and are relentless in their pursuit of perfection.
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.
Partner with data and platform engineers to ensure scalable deployment and monitoring.
Description
The Customer Support AI team is responsible for building multi-turn, conversational, agentic applications and frameworks to support Apple customers across numerous lines of business. You’ll be contributing hands on to a team that consists of engineers, data scientists & researchers to enhance a multi-modal, multi-agent platform with a key focus on incorporating research to improve, latency, cost and customer experience. This is an incredible opportunity to contribute innovation & research to a well established generative AI platform within Apple. There is a huge amount of opportunity and growth within this space!
Preferred Qualifications
Exposure to multi-agent orchestration frameworks in Rust and Python.
Familiarity with modern deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Experience with data preprocessing, tokenization, and pipeline automation.
Proficiency in machine learning libraries (transformers, datasets).
Strong problem-solving and collaboration skills, with the ability to learn quickly and adapt to production-grade systems.
Experience working with Multi-modal LLMs to enable Voice capabilities is a plus or prior experience with STT, TTS systems.
Experience with deploying to cloud environments (AWS, GCP, on-remote hybrid) is required.
Minimum Qualifications
5+ years of hands-on experience in ML, backend engineering, data engineering
1-2 years of hands-on experience in training, fine-tuning, or evaluating LLMs
Foundational understanding of RAG architectures and vector-based retrieval systems
Strong experience partnering with business and engineering team to deliver AI solutions
Bachelor's or Master's degree in Computer Science, Machine Learning, or related field, or equivalent practical experience.