Engineer (Machine Learning), Ops & Sales Engineering

Imagine what you could do here. At Apple new ideas have a way of becoming extraordinary products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could accomplish. Itʼs the diversity of those people and their ideas that inspires the innovation that runs through everything we do from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it!nnDo you want to help build some of the largest and most consequential enterprise and customer technology systems in the world Join Apples Information Systems and Technology (ISu0026T) organization. ISu0026T is the engine behind everything Apple does for customers and for the people who build for them. Its Apples central nervous system. Supporting 2.5 billion active Apple devices processing billions of secure transactions and keeping the technology that defines modern life running flawlessly ISu0026T makes the impossible feel you love building solutions to handle global complexity and immense scale Imagine what you could do here.

Sales and Operations Engineering is part of ISu0026T and drives the technology behind Apples global operations sales and supply chain. The team connects the systems that move products from factory to customer bridging sales platforms with the operational infrastructure that keeps Apple running at scale and ensuring Apples technology and business priorities move in are looking for a dynamic highly motivated experienced Applied Machine Learning Engineer with expertise and experience in GenAI for the Advanced Analytics team to join the ISu0026T Sales and Ops Apple the increasing supply chain complexity and scale presents unique challenges. This role is focused on applying GenAI and Machine Learning technologies to solve complex supply chain challenges within an enterprise context. The ideal candidate will have a proven track record of delivering scalable value-driven ML and GenAI solutions. You will be working with a team of experts responsible for designing and developing solutions leveraging advanced analytics (optimization ML simulation and GenAI) from strategic to executional decision-making and with engineering and application teams to integrate these solutions into our existing systems.

Design and develop advanced machine learning models several focusing on Generative AI to address specific supply chain use cases such as demand forecasting inventory optimization and logistics closely with cross-functional teams including engineering data science and application development to integrate analytics solutions into enterprise abreast of the latest advancements in machine learning and GenAI and explore innovative ways to apply these technologies to supply chain that analytics solutions are scalable and can be deployed across large complex enterprise big about the arc of development of GenAI over multi year horizon identity high ROI opportunities that will benefit from this technology and deliver critical partner teams to enable analytics data strategy and infra to support experimentation as well as robust deployment at enterprise scale. nCommunicate results and insights to partners and senior leaders technical and non-technical. Influence decision making with guidance and mentorship to team members and contribute to the overall growth of the analytics team.

MS in Computer Science Machine Learning Applied Math or a related field. n5 years of industry experience developing Machine Learning on experience in Python as programming deploying ML solutions to production.

PhD in Computer Science Machine Learning Applied Mathematics or a related field.n10 years of experience building and deploying production machine learning systems using Python C TensorFlow or expertise in machine learning deep learning NLP anomaly detection large language models and Generative AI including modern architectures retrieval-augmented generation fine-tuning prompt engineering and agentic designing deploying and evaluating reliable AI and agentic systems including tool use planning orchestration human-in-the-loop controls uncertainty and confidence estimation robustness factuality safety latency cost and end-to-end business with scalable data and ML infrastructure including SQL Spark graph databases cloud platforms and applying reinforcement learning NLP and Generative AI to operational logistics or supply chain ability to independently deliver high impact AI solutions from concept through production define meaningful KPIs and measure business communication and collaboration skills with the ability to explain complex technical concepts clearly work effectively across technical and business teams and build alignment around AI initiatives.