Apple is seeking a highly experienced ML Engineer to build, deploy, optimize, and operationalize Small and Large Language Model (LLM)-based applications. The role emphasizes MLOps/LLMOps and scalable production systems, requiring expertise in the full model lifecycle. The engineer will own the infrastructure and tooling necessary for reliable model deployment and monitoring at scale. This position also involves mentoring other engineers and setting technical standards within the team.

• Master's degree in Computer Science, Engineering, or a related field
• 8+ years of experience in Machine Learning and software engineering
• Proven track record of shipping production-grade ML/LLM systems
• Strong understanding of LLMs, fine-tuning, prompt engineering, and RAG patterns
• Experience building pipelines that process multimodal data and integrate ML model inference
• Hands-on experience deploying, serving, and optimizing LLMs or ML models in production
• Experience with vector search technologies and storing/serving embeddings
• Experience with feature stores and data lineage tracking
• Strong proficiency in Python and solid software engineering fundamentals
• Working proficiency in Java or Scala
• Experience with distributed systems and cloud platforms
• Experience with ML lifecycle management and versioning practices
• Experience with workflow orchestration platforms
• Excellent communication skills and a collaborative mindset
• Ph.D. in Computer Science, Machine Learning, or a related field
• Experience with Go
• Solid understanding of machine learning algorithms and data processing pipelines
• Active participation in open-source projects related to AI/ML
• Familiarity with graph databases
• Experience defining SLAs and observability standards for data platforms
• Track record of mentoring engineers and influencing technical direction
• Working knowledge of data privacy principles and practices
• Experience implementing model governance frameworks
• Experience implementing safety guardrails for LLM-powered systems
• Hands-on experience with observability and evaluation tools for LLMs

• Build, deploy, optimize, and operationalize LLM-based applications.
• Own the infrastructure and tooling for reliable model deployment and monitoring.
• Work across the full model lifecycle from experimentation to retirement.
• Build pipelines that ingest and enrich multimodal data.
• Deploy and operate services on cloud-native infrastructure.
• Optimize models for production through various techniques.
• Implement governance workflows, approval gates, and audit trails.
• Build safety guardrails to protect model outputs and user privacy.
• Mentor other engineers and help set technical standards.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.