onsite
Senior ML Production Model Automation Engineer - Apple
QA Engineer
Lead the automation of machine‑learning model deployment for a world‑class AI assistant, ensuring rapid, reliable, and privacy‑centric delivery across iOS, macOS, watchOS, and visionOS using Python, Docker, Kubernetes, and robust CI/CD pipelines.
About the role
Key Responsibilities
- Design, build, and maintain end‑to‑end pipelines that automate the training, validation, and deployment of ML models for voice and contextual AI features.
- Collaborate with research, data engineering, and product teams to translate prototype models into production‑ready services.
- Implement containerized (Docker) and orchestrated (Kubernetes) solutions that scale across Apple’s multi‑platform ecosystem.
- Develop and enforce CI/CD workflows, automated testing, and monitoring to ensure model quality, performance, and compliance with privacy standards.
- Continuously optimize model inference latency and resource utilization on edge devices.
Requirements
- 5+ years of experience in ML engineering with a focus on production deployment.
- Proficiency in Python, Docker, Kubernetes, and cloud‑native tooling.
- Strong background in CI/CD, automated testing, and observability for ML services.
- Experience with large‑scale, privacy‑centric AI systems is highly desirable.
- Excellent communication skills and a collaborative mindset.
Skills
machine learningpythondockerkubernetescicd