Senior AI/ML Engineer, Tools & Infrastructure

Apple•Cupertino, CA

About The Position

In this role you'll architect and implement AI/ML software applications and platforms for the Reliability department at Apple. You’ll provide technical leadership and bridge the gap between business needs and production software, delivering tools that automate workflows and surface novel insights for the organization.

Requirements

B.S. in Computer Science, Software Engineering, Computer Engineering, Machine Learning, or related field 4+ years experience and strong foundation in Software Engineering fundamentals, including data structures, algorithms, object-oriented design, and proficiency in building production-quality applications in Python
2+ years expertise in AI Engineering, using modern ML frameworks to design and deploy production-level platforms with end-to-end observability using vector-enabled data stores (e.g. Postgres/Timescale)
Demonstrated leadership experience with the ability to lead contractors, mentor peers, and manage technical resources effectively
Proven ability to drive projects independently: defining scope, collaborating with stakeholders, negotiating requirements, and driving projects to completion
Solid understanding of Machine Learning algorithms, with the ability to select and implement the right model or approach for the problem at hand
Excellent communication and presentation skills, with the ability to articulate complex technical concepts to diverse audiences and influence decision-making
Thrives in fast-paced, evolving environments—quickly pivots priorities while maintaining data integrity and reliability

Nice To Haves

M.S. in Computer Science, Software Engineering, Computer Engineering, Machine Learning, or related field
Passion for quality and attention to detail; proactive in researching and assessing emerging technologies (AI/ML models, protocols, and techniques), and integrating them into production
Experience designing and operating MLOps workflows in cloud-native environments, including CI/CD for ML systems, model versioning and promotion, scalable batch and online inference, and monitoring of data quality, model performance, and system reliability in production
Track record of successfully growing the scope of engineering projects from initial proof-of-concept to organization-wide adoption
6+ years experience and strong foundation in Software Engineering fundamentals, including data structures, algorithms, object-oriented design, and proficiency in building production-quality applications
Experience with Python (FastAPI), PyTorch, Hugging Face, and Spark to deploy production-level platforms on Kubernetes with end-to-end observability, MLflow tracking, and vector-enabled data stores (e.g. Postgres/Timescale)
Experience with computer vision technologies and techniques, especially for segmentation, anomaly detection, and objective grading is a plus