Applied Gen AI Engineer - Enterprise AI Platform

Apple, Inc.; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

Apple Inc. seeks an AI Data Platform expert to design, build, and evolve models, tools, and applications for enterprise AI experiences while prioritizing privacy and user trust. You will influence architecture and deployment strategies across backend services to enable reliable, scalable gen AI solutions.

You will contribute to production-grade models and platforms, tackling challenges in safety, privacy-preserving generations, and efficient inference, with strong collaboration across teams.

Qualifications

• 2+ years of hands-on applied AI/ML experience in industry or 4+ years in academia
• Expertise in generative AI, computer vision, NLP, or ML with a problem-solving mindset
• BS in CS/ML or equivalent; MS/PhD strongly preferred
• Experience with ML frameworks for training, fine-tuning, and deployment at scale
• Proven track record of enterprise-grade ML/Gen‑AI products in cloud or on‑prem environments

Responsibilities

• Design, build, and evolve models, tools, and applications powering high-impact AI experiences across the company
• Contribute to architecture and optimization of AI/gen AI systems for high availability, scalability, and reliability
• Work across backend services and application layers to deliver production-grade gen AI capabilities

Skills

Generative AI

Problem solving

Team collaboration

Education

BSc in Computer Science / ML

MS/PhD in ML/NLP/CV (preferred)

Tools

AWS/GCP/Azure

Job description

Apple Inc. seeks an AI Data Platform expert to design, build, and evolve models, tools, and applications for enterprise AI experiences while prioritizing privacy and user trust. You will influence architecture and deployment strategies across backend services to enable reliable, scalable gen AI solutions.

You will contribute to production-grade models and platforms, tackling challenges in safety, privacy-preserving generations, and efficient inference, with strong collaboration across teams.