Job Description

Apple's Generative AI team is looking for a creative and driven ML Engineer to help shape the future of AI-powered experiences across the enterprise. In this role, you will work on cutting-edge systems that enable large-scale training, inference, and deployment of generative models. If you are passionate about building production-grade ML systems, solving hard research-backed engineering problems, and contributing to innovations that impact millions of users, we want to hear from you.

Description

You are a creative problem solver with strong ML and engineering skills who thrives in a fast-paced environment, working across teams and organizations. You enjoy learning new technologies and have a deep interest in ML/GenAI models and systems. You take ownership of your work, communicate scope clearly, and are motivated by the impact your models and systems will have on real-world users. Most importantly, you care about building responsibly and sharing your learnings with the broader ML community. The main responsibilities for this position include:","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

Preferred Qualifications

Contributions to major open-source ML frameworks or research communities



MS or PhD in Computer Science, Machine Learning, or a related quantitative field



Solid grasp of NLP techniques, multimodal AI (text, image, code), and agent workflows.



Experience with LLM Agentic workflows and framework (Langchain, LangGraph, LlamaIndex, CrewAI etc.)



Knowledge in compiler/runtime optimizations for machine learning workloads

Minimum Qualifications

Bachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience



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)



Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .