AI/ML - Applied Research Engineer, Machine Translation

Apple • Seattle, WA

120d

About The Position

Apple's Machine Translation is embedded into several products across the iOS, iPadOS, macOS and watchOS ecosystems: from Translate App that is used to communicate across different languages to system-wide translation that allows you to quickly translate any highlighted text into an ever growing list of languages. Your role will be instrumental in applying and improving data and model training pipelines that allow for rapid expansion into supporting new languages and raising the bar for translation quality in shipped models. You will be part of a motivated and dynamic team that is responsible for managing data acquisition projects, training neural machine translation models, and driving evaluation criteria that help to establish an unprecedented translation quality in all of Apple's MT products.

Requirements

• Strong programming and software engineering skills (Python, C++, Java, or equivalent).
• Good ML knowledge and modeling expertise in the context of NLP applications such as LLM, MT, ASR.
• Experience with large scale data processing (Spark, or equivalent), data management and analytics.
• Ability to manage complex processes across multiple stakeholders.
• Excellent communication skills and team player.
• Motivation to build the best products for Apple's customers.

Nice To Haves

• 2+ years of experience in software engineering.
• Experience in building large scale ML systems.
• Distributed cloud computing experience (GCP, AWS).

Responsibilities

• Develop and optimize solutions to create, maintain and ship scalable and high-quality model assets for multiple languages.
• Apply and improve data and model training pipelines.
• Support rapid expansion into new languages.
• Raise the bar for translation quality in shipped models.
• Manage data acquisition projects.
• Train neural machine translation models.
• Drive evaluation criteria for translation quality.

What This Job Offers

• Number of Employees: 5,001-10,000 employees