2 days ago
Responsibilities
- Lead qualification of LLM inference and output-correctness automation frameworks for large-scale AI data center deployment and platform validation.
- Architect qualification systems for generative AI, including agentic workflows and tool-using models.
- Validate model outputs across changes to models, weights, prompts, serving runtimes, quantization schemes, and accelerator hardware.
- Build production-quality automation, evaluation, and AI-assisted QA tooling.
- Apply statistical and machine-learning evaluation methods to model and data behavior.
- Integrate automated evaluations into release pipelines and define quality standards for LLM inference.
- Partner with ML, inference/performance, distributed systems, and platform engineering teams.
Requirements
- At least 5 years of experience with hardware and/or software development lifecycle processes.
- At least 5 years of experience with one or more compiled languages such as C, C++, Objective-C, or Swift.
- Proficiency in a scripting language such as Python, Go, or JavaScript.
- Experience using AI or LLMs to improve testing through test-case generation, defect detection, or reduced manual QA effort.
- Familiarity with LLM serving, inference optimization, GPU-accelerated software, and distributed or multi-accelerator serving.
- Experience with Kubernetes, containers, cloud-native systems, and automated evaluation pipelines.
- Experience with machine learning and LLM frameworks such as PyTorch or Hugging Face Transformers, or comparable inference and serving stacks.
- Experience with observability, distributed tracing, and model-drift monitoring using tools such as Splunk, Prometheus, Grafana, or LangSmith.
- Bachelor's, master's, or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience.
- Preferred: at least 5 years working with and building operating systems.
- Preferred: at least 2 years of experience in LLM testing or development.
Tech Stack
CC++GoGrafanaHugging Face TransformersJavaScriptKubernetesObjective-CPrometheusPythonPyTorchSplunkSwift
Categories
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.