Infrastructure Engineer
Designs and operates high-performance inference and training infrastructure for ML models, focusing on GPU scheduling, distributed systems, and cloud optimization. Requires 2+ years experience with cloud platforms like AWS/GCP/Azure.
About the job
Responsibilities
- Architect and manage the infrastructure powering our ultra-fast inference and training stack.
- Build reliable, efficient systems for deploying and scaling ML workloads globally.
- Work on GPU scheduling, distributed systems, and high-performance cloud deployments.
- Optimize performance and cost across compute, networking, and storage layers.
- Collaborate with world-class engineers to push the limits of what small models can do.
Requirements
- 2+ years of experience writing high-quality production code
- Strong experience with cloud infrastructure (AWS, GCP, Azure, or equivalent)
- Experience with data science and systems optimization
- Familiarity with ML infrastructure, GPUs, etc. a plus
Skills
AWS, GCP, Azure, Kubernetes, Docker, Gpus, Distributed Systems, ML Infrastructure, Terraform, Linux
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