6 часов назад
Infrastructure Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Infrastructure Engineer (AI) (GPU platforms, distributed systems, and ML infrastructure): Building low-latency inference platforms, petabyte-scale data processing infrastructure, and GPU-based training clusters for world models with an accent on scalability, throughput, reliability, and efficient resource utilization. Focus on designing Kubernetes and Infrastructure as Code systems, tuning performance and cost, and improving researcher and developer workflows.
Location: Palo Alto, London, or Zurich
Company
is an AI lab developing causal, multimodal world models that learn to predict and interact with the world over long horizons.
What you will do
- Develop and operate a low-latency model inference platform with high availability, scalability, and efficient resource utilization.
- Build and scale data processing infrastructure using technologies such as Flyte and Ray on Kubernetes for petabyte-scale datasets.
- Design, build, and maintain large-scale GPU training clusters for deep learning with high usability, throughput, and reliability.
- Automate infrastructure provisioning, configuration, monitoring, and alerting using Infrastructure as Code principles.
- Drive performance tuning, cost optimization, and reliability improvements across the infrastructure stack.
- Collaborate with researchers and product developers to optimize workflows and improve platform usability.
Requirements
- Strong programming skills in Python, Go, or a similar language.
- Hands-on experience with Docker, Kubernetes, and Terraform.
- Experience building and managing large-scale distributed systems with GPU workloads.
- Experience designing infrastructure for machine learning workloads where performance, parallelism, and data movement are critical.
- Understanding of software engineering best practices.
- Collaborative mindset, strong communication skills, and interest in developer-friendly platforms.
Culture & Benefits
- Work on foundational AI infrastructure for world models and frontier research.
- Collaborate with researchers and product developers across a multidisciplinary engineering environment.
- Build infrastructure focused on speed, creativity, discovery, and real-time interaction.
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