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# Machine Learning Engineer (MLOps), Evaluation

- **Company:** Apple Inc.
- **Location:** Cupertino, CA, United States
- **Experience:** Experienced
- **Salary:** $147,400.0 - $272,100.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Systems Engineering, Microsoft Azure, Databases, Continuous Integration, Distributed Systems, Machine Learning, NoSQL, Performance Tuning, Software Engineering, SQL Databases, Management of Software Versions, Google Cloud, Large Language Models, Prompt Engineering, Model Validation, Backend, Kubernetes, Information Technology, Machine Learning Operations, Front End Software Development, Data Pipelines
- **Published:** May 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a84991c41842464d

## About the Role

Do you have experience in Systems engineering?, Do you have a Master's degree?, 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.

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.

## Description

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.","responsibilities":"Explore, design and implement advanced ML Infrastructure framework and tools.

Establish standard methodologies for model integration, deployment, and monitoring using CI/CD principles.

Ensure LLM services are scalable, efficient, and secure for high-traffic LLM services.

Champion model observability, incident response, prompt versioning, and feedback loops.

Use your ingenuity and creativity to resolve complicated and/or novel product and engineering challe

Implement processes and frameworks for the continuous quality improvement of Apple Intelligence, fostering excellence and reliability.

Work closely with data scientists, frontend engineers, product managers, and other stakeholders to define metrics, gather requirements, and deliver impactful solutions.


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