Machine Learning Engineer, Answers Knowledge and Information Proactive

The Information Intelligence team is creating groundbreaking technology for artificial intelligence machine learning and natural language processing! The features we create are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products including Siri Spotlight Safari Messages and Lookup. We also develop state-of-the-art generative AI technologies based on Large Language Models to power innovative features in both Apples devices and services on the cloud. As part of this group you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data) and Summarization as well as developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning and large language models (LLMs) to understand user queries retrieve and rank relevant documents across multiple sources and synthesize information across documents to provide user with a direct answer that best satisfies their intent and information seeking needs. Additionally you will research and develop the state-of-the-art LLMs for summarizing personal data such as emails messages and notifications. You will also work with researchers and data scientists to develop fine-tune and evaluate domain specific Large Language Models for various tasks and applications in Apples AI powered products and conduct applied research to transfer the cutting edge research in generative AI to production ready technologies.

As a member of our fast-paced group youll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for highly motivated machine learning engineers and researchers having strong machine learning and deep learning fundamentals with hands-on experience in fine-tuning deep learning and large language models.n

Conduct research and development on state-of-the-art deep learning and large language models for various tasks and applications in Apples AI-powered products nDeveloping 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 problemsnConducting applied research to transfer the cutting edge research in generative AI to production ready technologiesnUnderstanding product requirements translate them into modeling tasks and engineering tasks nStay up to date with the latest advancements and research in deep learning and large language models

Experience in modeling user behavior including personalization online learning and recommendation systemsnExperience working with machine 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 evaluationnExperience working with Python and at least one of the deep learning frameworks such as TensorFlow PyTorch or JAX

PhD in Computer Science Artificial Intelligence Machine Learning or a related least 2 years of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more of the following areas -- 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 guardrailsnConsistent track record of researching inventing and/or shipping advanced machine learning modelsnOutstanding communication and interpersonal skills with ability to work with cross-functional teams