Apple

Apple's WW Channel Strategy & Operations (CSO) organization focuses on developing and deploying worldwide sales programs and best practices to deliver an extraordinary customer experience in the channel and drive Apple Channel sales.. With deep functional expertise in digital, physical, and people enablement spaces, our WW CSO team closely collaborates with many cross-functional groups at world-wide and regional levels.. Practical experience in AI architecture and pipeline planning, with deep understanding of workflows associated with ML/deep learning projects and data science products (ex.. Deep expertise in data science and advanced analytics, including coding languages such as SAS, R, and Python and applied mathematics frameworks. Practical knowledge of ML and deep learning frameworks (TensorFlow) and ML algorithms or techniques such as random forest, neural networks, etc.

solutions architect

Summary Imagine what you could do here. The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's 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. Apple's WW Channel Strategy & Operations (CSO) organization focuses on developing and deploying worldwide sales programs and best practices to deliver an extraordinary customer experience in the channel and drive Apple Channel sales. With deep functional expertise in digital, physical, and people enablement spaces, our WW CSO team closely collaborates with many cross-functional groups at world-wide and regional levels. We are seeking an experienced AI Platform Solutions Architect to own the solution architecture and infrastructure design for our various AI & Decision Science Platforms. In this role, you will stitch together the expertise of data scientists/economists, data engineers, software developers, and product managers to deliver a high-performing, robust and industry-leading decision support engine. You will partner cross-functionally and multi-directionally with a variety of business unit leaders to understand uses cases and translate business requirements into technical solutions. As new technologies emerge, your impact will revolutionize how our channel teams use data to make decisions across every route-to-market. Key Qualifications 10-15+ years of experience in designing, building, and scaling data management platforms and AI/advanced solutions at global level Deep experience in owning decisions around AI architectural trade-offs between data management, governance, model building, deployment and product workflows Practical experience in AI architecture and pipeline planning, with deep understanding of workflows associated with ML/deep learning projects and data science products (ex. a/b testing with causal inference) Software engineering and DevOps expertise, including workflows and tools such as Git, containers, Kubernetes, and CI/CD Deep expertise in data science and advanced analytics, including coding languages such as SAS, R, and Python and applied mathematics frameworks Practical knowledge of ML and deep learning frameworks (TensorFlow) and ML algorithms or techniques such as random forest, neural networks, etc. Superior verbal and written communication and presentation skills, including the ability to convey advanced technology, mathematical, and engineering concepts and considerations to leadership, business partners, and technical teams Description In this role, you will: - Own the AI architecture strategy to develop various global decision science platforms that can efficiently and effectively scale with business needs and product launches - Understand real-world use cases to design an overarching technical plan that enables engineers and data scientists to develop in an agile capacity, considering work streams across data scientists, data engineers, developers, and operations (DevOps, DataOps, MLOps) - Develop processes and products that align technical implementation with existing and future business requirements by working across business teams, data scientists, ML engineers, developers, data engineers and analysts, security/privacy professionals, and system operations - Identify the appropriate technologies to best meet both short-term and long-term business and product needs, ensuring a system where new tools can integrate with existing data management and analytic tools - Continuously audit AI tools and practices across data, models, and software engineering to iterate and improve, implement feedback mechanism to assess product success - Remain current with AI security and data regulations to ensure best practices Education & Experience - Ph.D. in Computer Science, Machine Learning, or equivalent field; or - M.S. in related field with 5+ years of experience in software development and 3+ years of experience in AI solutions architecture

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