AIML - Linguistic Annotation Engineer, Safety & Red Teaming (apple)
apple Seattle, United States
2024-09-29
Job posting number: #151933 (Ref:apl-200563090)
This Job Posting is Expired.
Job Description
Summary
JOB IS FROM: partimejobs.netVIEWWould you like to play a part in building the next generation of generative AI applications at Apple? We’re looking for data scientists and engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world.
In this role, you’ll have the opportunity to tackle innovative problems in machine learning, particularly focused on LLM's. As a member of the Apple HCMI/Responsible AI group, you will be working on Apple's generative models that will power a wide array of new features, as well as longer term research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
In this role, you’ll have the opportunity to tackle innovative problems in machine learning, particularly focused on LLM's. As a member of the Apple HCMI/Responsible AI group, you will be working on Apple's generative models that will power a wide array of new features, as well as longer term research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
Description
Apple Intelligence is powered by high quality, detailed linguistic annotations. This role is instrumental in coordinating and documenting annotation projects with human annotators, data scientists, and machine learning engineers. Responsibilities include:
- Working with red teaming engineers to develop and create red teaming project strategies, interfaces, and guidelines
- Relaying and interpreting project guidelines and instructions for red teamers and annotators
- Serving as an interface for feedback and questions from red teamers and annotators back to data scientists
- Prioritizing and scheduling projects to align with organizational goals and timelines
- Working with data scientist and red teaming engineers to distill findings into recommendations for product engineering teams
- Monitoring and managing individual annotator performance metrics (accuracy, throughput, etc.) while providing feedback and guidance for improvement
- Working with red teaming engineers to develop and create red teaming project strategies, interfaces, and guidelines
- Relaying and interpreting project guidelines and instructions for red teamers and annotators
- Serving as an interface for feedback and questions from red teamers and annotators back to data scientists
- Prioritizing and scheduling projects to align with organizational goals and timelines
- Working with data scientist and red teaming engineers to distill findings into recommendations for product engineering teams
- Monitoring and managing individual annotator performance metrics (accuracy, throughput, etc.) while providing feedback and guidance for improvement
Minimum Qualifications
- Prior experience in linguistic annotation tasks including: Named-entity recognition, part-of-speech tagging, constituency parsing, dependency parsing, or application-specific natural language parsing
- Strong understanding of English language (linguistics, syntax, grammar) and its applications to Natural Language Processing
- Experience working on crowd-based annotations projects
- Experience developing, implementing, and communicating a sophisticated ontology or taxonomy system
- Project management expertise: Ability to collaborate with team members to prioritize competing projects, set and maintain a schedule for milestones and project completions, communicate with all levels of engineers, in-house annotators, and remote/crowd-workers
- Work with highly-sensitive content with exposure to offensive and controversial content
Key Qualifications
Preferred Qualifications
- BS, MS, or PhD in Linguistics or similar field and 2+ years experience as linguistic annotator
- Prior Teaching experience
- Experience interacting with LLMs (even if just for fun) and up-to-date knowledge of the kinds of issues that can occur with LLMs
- Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable
- Curiosity about tech and the way in which things can go wrong
