Machine Learning Research Engineer, Natural Language Generation (NLG)

Cupertino, California, United States
Software and Services

Summary

Posted:
Weekly Hours: 40
Role Number:200565038
On the Input Experience NLP team, we build the language models that underpin intelligent text input across Apple platforms, from keyboard auto correction to the Writing Tools and Smart Reply features announced at WWDC 2024. We believe that generative AI is an incredibly promising technology that can help people communicate effectively and express themselves clearly, and we have only just begun to incorporate this technology into our products. On our team, you will help build the future and have a voice in what shape it takes. We are looking for a Machine Learning Research Engineer to help deliver scalable, multilingual NLP solutions that empower our users to use intelligent text input in their language of choice. You will build and refine the training and evaluation pipelines that define our slice of Apple Intelligence, driving the focused iteration that makes the user experience magical. You will join an ambitious, organized, and collaborative team in a unique position to integrate the latest innovations from the ML community and work on features that reach everyday users, including your family and friends. You’ll work closely with teams across Apple, collaborating on human interfaces, user studies, internationalization, ML technologies, system integration, and more.

Description

As a Machine Learning Research Engineer on our team, you will build and iteratively refine model pipelines that enable multilingual text input experiences on Apple products. You will conduct experiments and create prototypes for new approaches to improve the quality of our models add new dimensions to their intelligence, in consideration of specific linguistic requirements and design considerations. Finally, you will implement the building blocks and infrastructure that bring these innovations into our production pipelines, and contribute evaluate metrics for measuring forward progress. KEY RESPONSIBILITIES: - Development and maintenance of modeling pipelines that scale to multiple languages and production deployment - Definition of robust automated evaluation metrics to facilitate hillclimbing model quality - Failure analysis to understand shortcomings of our models - Research into techniques for improving model behavior - Curation and synthesis of representative training and evaluation data - Implementation of experiments and simulations to assess the value of model changes - Collaboration with language experts and QA to refine modeling approach in consideration of language-specific requirements

Minimum Qualifications

  • MS or PhD in Computer Science or related field with at least 2 years of industry experience
  • Strong Python programming skills, with experience developing production-quality Python modules
  • Solid background in machine learning, data science, natural language processing, or statistics

Key Qualifications

Preferred Qualifications

  • Experience building and maintaining model pipelines end-to-end, from data curation to evaluation
  • Ability to design and perform experiments that bring ML and NLP research ideas to production
  • Familiarity with LLMs, such as SFT, RHLF, prompt engineering, data synthesis, automatic evaluation, and RAG
  • Background in linguistics, fluency in multiple languages, or a passion for scaling NLP features for global audiences
  • Excellent written and verbal communication skills
  • History of developing Python packages and supporting other users
  • Record of publications, innovations, and/or leadership

Education & Experience

Additional Requirements

Pay & Benefits

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.