Apple's Generative AI team is looking for an ML Engineer to help shape the future of AI-powered experiences across the enterprise by working on cutting-edge systems for large-scale training, inference, and deployment of generative models.
Requirements
- 2+ years of hands-on experience in machine learning engineering
- 1+ years focused on generative AI or LLM technologies, or Agentic workflows
- Solid experience in Python
- Experienced building ML frameworks (PyTorch, JAX) for training, fine-tuning, and deploying generative models at scale
- Experience building enterprise-grade ML pipelines (data prep, distributed training, optimization, monitoring) in cloud environments (AWS, GCP, Azure) or on-prem infrastructure
- Deep understanding of transformer architectures, prompt engineering, retrieval-augmented generation (RAG), and LLM evaluation methodologies
- Experience optimizing models for latency, cost, and scalability (quantization, distillation, hardware-aware ML)
Responsibilities
- Develop ML/GenAI models and pipelines to solve for business KPIs at scale
- Innovate training pipelines using cutting-edge distributed systems and hardware-aware optimization
- Partner with cross-functional teams to translate groundbreaking research into user-centric products
- Tackle unique challenges in privacy-preserving generation, efficient inference, and multimodal integration
- Deliver production-grade models that meet Apple’s rigorous standards for quality, performance, and scalability
Other
- Creative problem solver with strong ML and engineering skills who thrives in a fast-paced environment, working across teams and organizations.
- Enjoy learning new technologies and have a deep interest in ML/GenAI models and systems.
- Take ownership of your work, communicate scope clearly, and are motivated by the impact your models and systems will have on real-world users.
- Care about building responsibly and sharing your learnings with the broader ML community.
- Base pay range for this role is between $181,100 and $318,400
