The AIML Information Intelligence team at Apple is looking to solve the problem of improving Open Domain Question Answering and Summarization using large scale machine learning and deep learning research and development, as well as developing state-of-the-art generative AI technologies based on Large Language Models to power innovative features in Apple’s devices and services.
Requirements
- Experience working with Deep learning or LLM model development for various NLP tasks and RAG applications including prompt engineering, training data collection and generation, model fine-tuning and model evaluation
- Experience working with Python and at least one of the deep learning frameworks such as TensorFlow, PyTorch, or JAX
- Supervised Fine-tuning (SFT) with Rejection Sampling
- Preference-based fine-tuning techniques (e.g RLHF, Reward model, DPO, PPO, GRPO etc.)
- Parameter efficient fine-tuning techniques (e.g LoRA)
- Hallucination reduction and factual accuracy improvements
- Designing and implementing safety guardrails
Responsibilities
- Conduct research and development on state-of-the-art deep learning and large language models for various tasks and applications in Apple’s AI-powered products
- Developing, fine-tuning, and evaluating domain-specific Large Language Models for various NLP tasks including summarization, question answering, search relevance/ranking, entity linking and query understanding problems
- Conducting applied research to transfer the cutting edge research in generative AI to production ready technologies
- Understanding product requirements, translate them into modeling tasks and engineering tasks
- Stay up to date with the latest advancements and research in deep learning and large language models
- Develop large scale machine learning and deep learning models to improve Open Domain Question Answering and Summarization
- Research and develop state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications
Other
- Master’s in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field (preferred)
- Outstanding communication and interpersonal skills with ability to work with cross-functional teams
- At least 1 year of experience in various state-of-the-art techniques related to LLM fine-tuning
- At least 4 years of experience with large-scale model training, optimization, and deployment
