AIML - Staff Machine Learning Engineer

2 Months ago • All levels • Research Development

Job Summary

Job Description

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems. We are looking for candidates with both applied machine learning experience and strong engineering skills. The role involves owning the entire ML development cycle, from opportunity analysis and prototyping to data collection, feature engineering, training, evaluation, and deployment in production. The candidate will also lead the development of machine learning models to improve search quality and mentor junior engineers.
Must have:
  • Own the entire ML development cycle.
  • Lead development of machine learning models.
  • Improve search quality with various ML techniques.
  • Translate product requirements into modeling and engineering tasks.

Job Details

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems. We are looking for candidates with both applied machine learning experience and strong engineering skills. The role will have the following responsibilities: - Own the entire ML development cycle from opportunity analysis, exploration, and prototyping to data collection, feature engineering, training, evaluation, and deployment in production. - Lead the development of machine learning models to improve search quality across retrieval, ranking, reranking, and query understanding. - Improve search quality and experience by leveraging techniques such as learning-to-rank, embedding models, contrastive learning, multi-task learning, and reinforcement learning where appropriate. - Mentor junior engineers and provide technical leadership in architecting ML systems and designing ML models. - Understand product requirements, then translate them into modeling tasks and engineering tasks.

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