Are you passionate about frontier AI technology and driving its implementation into real-world products? As part of Apple's AI and Machine Learning org, we inspire and create groundbreaking technology for large language models, multi-modal models, with strong agent and reasoning capabilities, that will redefine user experiences globally. We are seeking a visionary and proactive Machine Learning Engineer to explore novel methods, develop new insightful practices, and drive the end-to-end lifecycle of data-modeling-evaluation. In this role, you will play a pivotal role in integrating cutting-edge foundation models into our next-generation AI products. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to create a significant impact for billions of users worldwide.
Description
As a Machine Learning Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art technology in foundation models to tackle complex problems. The solutions you develop will significantly impact future Apple products and the broader ML development ecosystem. You will work with a multidisciplinary global team to actively participate in the data-modeling-evaluation co-design and co-development practice. Your responsibilities will extend to the design and development of data curation pipelines, advanced modeling methodologies and effective evaluation metrics. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.
Preferred Qualifications
Staying up-to-date with emerging trends in generative AI.
Proven track record of successfully shipping AI/ML features into large-scale, real-world consumer products.
Publications in premier academic venues (e.g., NeurIPS, ICLR, ICML, CVPR) demonstrating research acumen, coupled with strong engineering execution.
Demonstrated leadership in advancing machine learning research and development, including driving innovative projects, mentoring team members, or leading collaborations that resulted in impactful outcomes.
Exceptional critical-thinking, problem-solving and communication skills, with a proven ability to break down complex, ambiguous open-ended problems into actionable engineering solutions.
Minimum Qualifications
Demonstrated expertise in machine learning, specifically in natural language processing, multi-modal foundation models, agent and reasoning capabilities.
Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX.
Hands-on practice in data curation, scalable training/fine-tuning, and comprehensive evaluation, with a strong emphasis on real-world production.
5-10 years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality.
BS/MS/PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Natural Language Processing, Computer Vision or equivalent practical experience, with 5-10 years of relevant industry experience.
