Роль четко определена с ясным акцентом на инфраструктуру машинного обучения, но широкий диапазон зарплаты вызывает вопросы о ее стабильности.
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Текст:
Hirify AI/Оригинал
TL;DR
Machine Learning Infrastructure Engineer (AI): Designing, building, and maintaining training and serving infrastructure for ML research with an accent on maximizing GPU allocation and utilization. Focus on diagnosing cluster issues, managing experiments, and supporting ML research.
Location: Hybrid in Redwood City, California, United States
Salary: $150,000–$350,000 annual base salary, plus equity
Company
Character.AI develops an interactive entertainment platform that enables users to connect, learn, tell stories, and interact with AI-powered characters.
What you will do
Provide infrastructure support for ML research and product systems.
Build tools to diagnose cluster issues, hardware failures, and other ML infrastructure problems.
Monitor deployments and manage research experiments.
Maximize GPU allocation and utilization for model serving and training.
Requirements
4+ years of experience supporting infrastructure in an ML environment.
Experience developing diagnostic tools for ML infrastructure problems and failures.
Experience with cloud platforms such as Compute Engine, Kubernetes, and Cloud Storage.
Experience working with GPUs.
Nice to have
Experience with large GPU clusters and high-performance computing or networking.
Experience supporting large language model training.
Experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
Experience developing GPU kernels.
Culture & Benefits
Hybrid work environment with daily in-office catering.
Health coverage for employees and families, with most of the premium covered.
401(k) contribution.
Up to 20 weeks of paid parental leave.
Four weeks of paid time off, monthly wellness support, and a monthly DoorDash stipend.
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