Software Engineer, Applied AI

Full-stack builders come join a creative engineering team devoted to making our products more durable through data-driven insights. Were looking for an Applied AI engineer to develop intelligent applications and systems that unlock the power of our hardware test data and enable hardware engineers to create their own software this role youll build scalable software to help take our departments capabilities to the next level. Youll work with hardware and software engineering teams throughout Apple to design robust AI/ML applications implement production-grade software and AI pipelines iterate based on evolving requirements and provide input on technical strategy. The tools and platforms you build will power processes analytics and workflows that directly influence the design of future products. This is a hands-on work environment where engineers are expected to be self-motivated and proficient with a wide range of AI/ML technologies while dedicating time to supporting contractors driving projects forward presenting to leadership and delivering excellent solutions for Apple.n

In this role youll implement AI/ML software applications at cloud-scale for the Reliability department at Apple. Youll bridge the gap between business needs and production software delivering tools that automate workflows and surface novel insights for the organization. nn

Implement robust full-stack GenAI-oriented applications using modern software engineering best practices including a Python/FastAPI backend a React/ TypeScript frontend AWS RDS and ElastiCache data stores and containerized deployments on AWS EKS with Helm and and maintain a multi-tenant EKS platform that enables users to build deploy and run their own applications in Kubernetes pods with integrated build pipelines sidecars and session-affinity reverse proxy at 5000 pod and integrate GenAI capabilities into the platform including agentic workflows AI agent skills LLM-powered web features and production-grade inference the scope of engineering projects moving through the full project lifecycle from concept to deploymentnCollaborate with a team of external contractors providing code reviews and support to ensure fast high-quality and operate production observability with OpenTelemetry tracing Prometheus metrics and structured logging to ensure application reliability and performance.

B.S. in Computer Science Software Engineering Computer Engineering Machine Learning or related to software engineering through internships with strong foundation in CS fundamentals including data structures algorithms and exposure to building web applications using Python (FastAPI SQLAlchemy) TypeScript (React/) and containerized services on Kubernetes (EKS Helm Terraform).nExposure to applied AI Engineering building software leveraging GenAI and ML to create production-level solutions to business needs and enhance organizational and development workflows.n Ability to follow direction from engineering lead for feature scope ability to collaborate with stakeholders review and refine requirements moving project towards communication and presentation skills with the ability to articulate technical concepts to diverse audiences while thriving in a fast-paced evolving environment.n

Passion for quality and attention to detail; proactive in researching and assessing emerging technologies (AI/ML models protocols and techniques) and integrating them into to multi-tenant platforms that execute user-submitted code including container image builds workload isolation RBAC systems and secure callback architectures is a building or integrating agentic AI systems LLM tool-use patterns or AI-assisted development to production observability stacks: OpenTelemetry Prometheus structured logging distributed tracing and dashboarding tools such as record of successfully growing engineering projects from initial proof-of-concept to organization-wide production foundation in Software Engineering fundamentals including data structures algorithms object-oriented design through school projects or with computer vision technologies and techniques especially for segmentation anomaly detection and objective grading is a plus.