Machine Learning Engineer, Proactive

Apple Apple · Big Tech · Cupertino, CA +1 · Machine Learning and AI

Machine Learning Engineer focused on developing, fine-tuning, and evaluating Large Language Models for various NLP tasks like summarization, question answering, and search relevance, with a strong emphasis on transferring cutting-edge generative AI research into production-ready technologies for Apple's AI-powered products.

What you'd actually do

  1. 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
  2. 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
  3. Conducting applied research to transfer the cutting edge research in generative AI to production ready technologies
  4. Understanding product requirements, translate them into modeling tasks and engineering tasks
  5. Stay up to date with the latest advancements and research in deep learning and large language models

Skills

Required

  • Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field
  • 10 years of work experience in machine learning, deep learning or related field
  • modeling user behavior including personalization, online learning and recommendation systems
  • 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 evaluation
  • Python
  • TensorFlow, PyTorch, or JAX

Nice to have

  • PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • 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 guardrails
  • 10 years of experience leading complex cross-functional projects and influencing research direction
  • 10 years of experience with large-scale model training, optimization, and deployment
  • Outstanding communication and interpersonal skills with ability to work with cross-functional teams

What the JD emphasized

  • fine-tuning deep learning and large language models
  • model fine-tuning
  • large-scale model training, optimization, and deployment
  • shipping advanced machine learning models

Other signals

  • large scale machine learning and deep learning research and development
  • state-of-the-art generative AI technologies based on Large Language Models
  • developing fundamental building blocks needed for Artificial Intelligence
  • understand user queries, retrieve and rank relevant documents across multiple sources and synthesize information across documents to provide user with a direct answer
  • research and develop the state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications
  • develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple’s AI powered products
  • transfer the cutting edge research in generative AI to production ready technologies