What are the responsibilities and job description for the Machine Learning Engineer (MLOps), Evaluation position at Apple?
We are seeking a highly experienced Machine Learning Engineer to build, deploy, and optimize Large Language Model (LLM)-based applications, with a strong emphasis on MLOps/LLMOps (LLM operations) and scalable production systems. At Apple, we believe in creating technology that enriches lives and empowers creativity. You’ll play a pivotal role in developing Apple Intelligence, driving the next generation of groundbreaking products across all Apple platforms.
The team is a growing group that works closely with product, ML research, Data Science and infrastructure teams, to ensure the successful delivery of Apple Foundation models and Apple Intelligence evaluations. We are looking for a Machine Learning Engineer focusing on MLOps/LLMOps infrastructure to build a next generation LLM-powered evaluation systems. In this role, you will be instrumental in scaling our internal evaluation platform, building automation and self-service tools, and ensuring the reliability and efficiency of large-scale LLM services. You will have the opportunity to create huge impacts across all AI products through innovations.
Minimum Qualifications:
4 years in software engineering with experience in large-scale software system design and implementation.
Proven track record of shipping production-grade ML/LLM systems.
Strong understanding of LLMs, fine-tuning, prompt engineering, vector databases and RAG patterns.
Experience with distributed systems, databases (SQL/NoSQL), cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes).
Ability to tackle complex challenges, think critically, and deliver innovative solutions.
Excellent communication skills and a team-oriented attitude, thriving in a collaborative and fast-paced environment.
Bachelor’s degree in Computer Science, Engineering, or a related field.
Preferred Qualifications:
Hands-on experience with observability and evaluation tools for LLMs.
Solid understanding of machine learning algorithms, model evaluation metrics, and data processing pipelines.
Previous experience in a high-growth tech company or similar environment.
Active participation in open-source projects related to AI/ML or backend development.
Master or Ph.D. in a related field.