AIML - Senior ML Researcher in Foundation Models, Responsible AI

Join us as we build world-class groundbreaking products for our customers! Apples Responsible AI and Safety team is looking to hire a technical lead with a strong track record in Applied Research who is passionate about ML and foundation models with a focus on responsibility, fairness, and safety. In this role, you will lead the research and application of ML methods for technologies that power breakthrough user experiences while upholding Apples values, privacy, and quality standards.

This role will be highly multifunctional. You will collaborate closely with top machine learning researchers and engineers, software engineers, and design teams to develop and deliver groundbreaking solutions for Apple products. We believe that the most exciting problems in machine learning research arise at the intersection of emerging technologies and real-world use cases. This is also where the most critical breakthroughs come from. As a researcher, you will:

• Define and deliver responsible machine learning technologies
• Develop methods and frameworks to train and evaluate foundation models with responsibility and safety in mind
• Research and advance safety alignment and model robustness methods for foundation models
• Research and develop mitigations and safeguards to ensure safe deployment of LLM's in Apple products
• Advocate for scientific and engineering excellence by contributing to the architecture and high-level structure of Apples AI-powered platform and features
• Work multi-functionally on a diverse set of challenging problems and collaborate with extraordinary software engineers, machine learning engineers, and researchers to impact the future of Apple products
• Work closely with product and partner teams to drive requirement definition, technical quality of deliverables, and execution

4+ Years research or product deployment record in areas related to responsible AI, with publications in top ML venues (e.g., ACL, CHI, CVPR, EMNLP, FAccT, ICML, Interspeech, NeurIPS, UIST, etc.)

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

Strong research fundamentals, machine learning principles, and development methodologies around LLMs, foundation models, and diffusion models

Proficient programming skills in Python and deep learning toolkits (e.g. JAX, PyTorch, Tensorflow)

Work with highly-sensitive content with exposure to offensive and controversial content

Strong organizational and operational skills working with large, multi-functional, and diverse teams

Experience with LLM training and safety alignment

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