AIML - Machine Learning Engineer/Scientist, Siri and Information Intelligen

at  Apple

SUMMARY

Posted: Jun 12, 2024
Role Number:200554814
The AIML 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 Apple’s devices and services on the cloud. As part of this group, you will be doing large scale machine learning and deep learning to improve Open Domain Question Answering and 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. 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 Apple’s AI powered products and conduct applied research to transfer the cutting edge research in generative AI to production ready technologies.

DESCRIPTION

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for people with excellent applied machine learning experience and solid engineering skills in creating outstanding question answering service. This role will have the following responsibilities: -Analyzing search ranking and relevance requirements, issues and opportunities -Developing, fine-tuning, and evaluating domain-specific Large Language Models for various tasks and applications in Apple’s AI-powered products -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 -Building machine learned models for question answering, search relevance, ranking and query understanding problems -Integrating search functions into Apple products, such as Siri, Spotlight, Safari, Messages, Lookup, etc. -Building end-to-end production system including query understanding and ranking to power search and open domain question answering -Utilizing Spark, Hadoop MapReduce, Hive, Impala to perform distributed data processing

• Experience in machine learning, deep learning/LLM, information retrieval, natural language processing
• Experience of prompt engineering, fine-tuning, evaluating, and developing data collection/annotation/management tooling for LLMs.
• Proficiency in Python and at least one of following languages: Go, Java, C++
• Excellent knowledge and good practical skills in major machine learning algorithms
• Excellent data analytical skills
• Good interpersonal skills and team player

PREFERRED QUALIFICATIONS

• Experience with Large Scale Data-Mining and/or Machine learning are a plus
• Experience with ML and LLM model inference optimization is a plus
• MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field

• Experience in machine learning, deep learning/LLM, information retrieval, natural language processing
• Experience of prompt engineering, fine-tuning, evaluating, and developing data collection/annotation/management tooling for LLMs.
• Proficiency in Python and at least one of following languages: Go, Java, C++
• Excellent knowledge and good practical skills in major machine learning algorithms
• Excellent data analytical skills
• Good interpersonal skills and team playe