AIML - Senior Applied ML Engineer, DMLI

Pittsburgh, Pennsylvania, United States
Machine Learning and AI


Role Number:200536741
Home Office: Yes
Would you like to play a part in building the next generation of generative AI applications at Apple? We’re looking for 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 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 such models.

Key Qualifications

  • Hands-on experience in pioneering machine learning and deep learning as applied to large-scale datasets
  • Background in generative models, natural language processing, and LLMs
  • Strong engineering skills and experience in writing production-quality code in Python, Swift or other programming languages
  • Experience in prompt engineering, fine-tuning, evaluating, and developing data collection/annotation/management tooling for large language models.
  • Ability to work in a diverse and collaborative environment


- Prototype, implement, and evaluate new ML models and algorithms for red teaming LLMs - Implement and build machine learning models that mitigate the risks associated with LLMs - Develop tools, metrics, and datasets for assessing and evaluating the safety of LLMs over the model deployment lifecycle, as well as methods and tools to help interpret and explain failures in language models. - Build and maintain human annotation and red teaming pipelines to assess quality and risk of various Apple products

Education & Experience

BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues

Additional Requirements