Machine Learning Engineer, Natural Language Generation (NLG)
Job Description
Summary
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 Engineer to help our ML models grow even smarter and reason about personal context in a privacy-preserving way. 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.
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something—you’ll add something.
We are looking for a Machine Learning Engineer to help our ML models grow even smarter and reason about personal context in a privacy-preserving way. 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.
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something—you’ll add something.
Description
As a Machine Learning Engineer on our team, you will build and iteratively refine model pipelines that define the intelligent behaviors built deeply into the text input experience on Apple products. You will conduct experiments and create prototypes for new approaches to improve the quality of our models and add new dimensions to their intelligence. Finally, you will implement the building blocks and infrastructure that bring these innovations into our production pipelines.
KEY RESPONSIBILITIES:
Development and maintenance of modeling pipelines that scale to deployment in production
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
KEY RESPONSIBILITIES:
Development and maintenance of modeling pipelines that scale to deployment in production
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
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
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
- Excellent written and verbal communication skills
- History of developing Python packages and supporting other users
- Record of publications, innovations, and/or leadership
- Background in linguistics, fluency in multiple languages, or a passion for scaling NLP features for global audiences
Pay & Benefits
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