WW Consulting Engineer - AI​/ML

Chicago, Illinois, United States Sales and Business Development

In this role, you will:

• Empower and educate global Field Sales Engineers, customers, and partners on Apple’s product advantages — Mac, iOS, iPadOS, Apple Silicon — across cloud-based, hybrid, on-device, and edge AI/ML architectures, with fluency in where each deployment model is most appropriate.
• Develop and articulate compelling technical value propositions for Apple platforms across enterprise, education, and government sectors, with particular depth around Apple Foundation Models (AFM), on-device inference, and Apple Intelligence features.
• Collaborate with cross-functional teams — including Product Marketing, Business Markets, Engineering, and Sales Leadership — to define and refine go-to-market strategies and AI/ML solution offerings leveraging Apple technology.
• Engage directly with strategic customers and partners in deep technical discussions, understanding their AI/ML initiatives and positioning Apple’s unique capabilities — including Private Cloud Compute (PCC) privacy guarantees — to meet their needs and drive innovation.
• Advise on scalability strategies for on-device and edge AI/ML solutions, determining when a single node is sufficient versus when a cluster approach is necessary, including hardware selection and model serving architecture for sovereign AI deployments.
• Guide enterprise customers and developers on integrating AI/ML capabilities into applications using approaches such as Model Context Protocol (MCP) and App Intents, and how to evaluate tradeoffs between them.
• Monitor and analyze emerging AI/ML trends, technologies, and industry shifts — translating insights into actionable guidance for field teams and leadership, with a continuous learning mindset.
• Lead key customer and partner engagements including executive briefings, workshops, proof-of-concepts, and technical presentations showcasing Apple’s leadership in the AI/ML space.
• Contribute to technical resources, training modules, and best practices that scale AI/ML knowledge and capabilities across the global sales organization.
• Drive thought leadership internally and externally on the transformative impact of AI/ML on work and learning, with a focus on Apple’s contributions and advantages.

Note:

This role requires periodic domestic and international travel.

• 7+ years of experience in a highly technical, customer-facing AI/ML role — such as a Solutions Engineer or Solutions Architect at a major cloud provider; a Field CTO, Technical Evangelist, or Field Engineer at an AI platform or foundation model company; or a Principal Technical Consultant at an enterprise technology organization.
• Deep and demonstrable expertise in AI/ML concepts and applications, including:
  • Machine learning algorithms (supervised, unsupervised, reinforcement learning)
  • Deep learning architectures (CNNs, RNNs, Transformers, diffusion models)
  • MLOps principles, data science methodologies, and model deployment strategies
  • Hands-on experience with major cloud AI/ML platforms (e.g., AWS Sage Maker, Azure ML, Google AI Platform)
• Deep, hands-on knowledge of Apple’s on-device AI/ML stack, including:
  • Understanding of Apple Silicon architecture and its benefits for on-device inference and other AI/ML workflows
  • Apple Foundation Models (AFM) and their capabilities and appropriate use cases
  • Core ML, Core ML Tools, and related on-device inference frameworks
  • Private Cloud Compute (PCC) architecture and privacy guarantees
  • Strong ability to articulate the distinction between on-device inference, Private Cloud Compute, and third-party cloud-hosted models — and when each is the right architecture for a given use case.
• Demonstrated ability to engage directly with large organizations and partners on strategic AI/ML opportunities, advocating for Apple’s platform advantages in real-world use cases.

• Experience collaborating with product management, software engineering, and hardware engineering teams to influence platform direction and roadmap priorities.
• Hands-on experience with MLX for training, fine-tuning, and running inference with LLMs and other model types on Mac…