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Apple Sr Applied ML Engineer Wallet & Payments United States, New York, New York 738959691
Today
We are seeking a talented Senior Applied ML Engineer to lead and contribute to high-visibility projects. You will be at the forefront of designing and developing cutting-edge AI/ML models and GenAI applications, working with our AI/ML engineers on a wide spectrum of approaches to improve the user experience in Wallet and other services. This role requires deep expertise in Machine Learning, a passion for transforming ideas into products, and the ability to effectively communicate complex ideas to cross-functional teams and partners. IN THIS ROLE, YOU WILL:- Design and implement advanced Machine Learning models to optimize user experiences across Wallet services, including Pay, Cash, and Card. - Develop and evaluate prototypes, proof-of-concepts, and production-ready solutions.- Effectively communicate analytical insights to partners and senior leaders, providing clear, actionable recommendations - Research and develop techniques for efficient on-device ML.
- PhD/MS in Computer Science, Machine Learning, Information Technology, Computational Linguistics, NLP, Computer Vision, Statistics, Applied Math or a related field, or equivalent work experience.
- Expertise and experience in various facets of machine learning and natural language processing, such as feature engineering, classification, information extraction, clustering, semi-supervised learning, topic modeling and ranking.
- Experience with computer vision or vision-language models.
- Proven record in delivering end-user facing ML driven products.
- Experience with model deployment pipelines and serving GenAI models in production.
- Strong programming experience in one or more of the following: Python, Scala, Swift
- Expertise in at least one deep learning framework, eg: PyTorch, TensorFlow, or Jax
- Attention to detail, data accuracy and quality of output.
- Strong problem-solving skills and the ability to tackle novel challenges, combined with strong communication and interpersonal capabilities.
- Highly self-motivated and results-driven, able to operate independently and lead without authority.
- Hands-on experience working with transformer-based architectures, e.g., GPT, BERT.
- Hands-on experience with RAG, LLM fine-tuning.
- Familiarity with GenAI frameworks and tools, e.g., LangChain.
- Prior team lead experience is desired.
- Familiar with model compression algorithms including quantization, pruning, distillations, and experience on optimizing large language models.
- Familiarity with reinforcement learning and advanced optimization techniques.
- Strong understanding of state-of-the-art LLMs and deployment for real-world applications.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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