Staff Engineer, Distributed Storage & AI Infra

Salary: $250,000 - 300,000 per year Requirements:

• We need 8+ years of experience in storage engineering, including operating distributed storage at multi-petabyte scale
• We look for a proven background in deploying and running high-performance storage for GPU or HPC clusters
• We require deep production experience with Kubernetes and cloud-native storage
• We expect strong Go and Python programming skills with the ability to build production-grade systems and tooling
• We require a BS/MS in Computer Science, Engineering, or equivalent practical experience
• We value technical leadership that has improved performance, reliability, or cost efficiency at scale
• We need deep expertise in distributed storage systems such as Ceph, WekaFS, Lustre, Vast, GPFS, or similar parallel filesystems
• We expect production experience with object storage such as S3, MinIO, Ceph, or R2, including performance tuning and cost control
• We require experience with Kubernetes storage components such as CSI drivers, StatefulSets, PersistentVolumes, storage operators, and custom controllers
• We need experience optimizing storage for GPU workloads and working with RDMA/InfiniBand networking and parallel filesystem performance
• We require automation and tooling experience with Go and Python
• We expect infrastructure-as-code experience with Terraform, Ansible, Helm, and GitOps using ArgoCD
• We need advanced knowledge of the Linux storage stack, including ext4, xfs, LVM, NVMe tuning, and RAID configurations
• We expect observability experience with Prometheus, Grafana, and Thanos
• Nice-to-have experience includes GPU Direct Storage, NVMe-oF, storage networking, and RDMA implementations
• Nice-to-have familiarity with ML/AI storage patterns such as model weights, checkpointing, and dataset caching
• Nice-to-have experience with storage benchmarking and profiling tools such as fio, iperf3, iostat, and blktrace

• We will define and drive the technical strategy and storage roadmap for Together AI as we expand our GPU fleet
• We will engineer and scale multi-petabyte AI/ML storage systems by integrating Vast, Weka, and Ceph while reducing cost through automated tiering and lifecycle policies
• We will design intelligent caching and tiered storage architectures to deliver extreme IOPS and cluster-wide throughput for training and inference workloads
• We will tune storage isolation at the L2/L3 network layers to provide secure, production-ready multi-tenancy for storage clients
• We will build Kubernetes storage operators and controllers that enable automated provisioning, self-service workflows, and quota enforcement
• We will optimize end-to-end data paths to achieve 10+ GB/s per GPU node, architect multi-tier caching for model weights and datasets, tune parallel filesystems with advanced profiling, and scale storage across thousands of nodes
• We will improve data paths through advanced benchmarking and profiling, while contributing high-impact code to open-source storage projects and internal tooling

• AI
• Ansible
• Architect
• ArgoCD
• Cloud
• Ceph
• GitOps
• Grafana
• Hardware
• Helm
• InfiniBand
• Kubernetes
• Linux
• Network
• Prometheus
• Python
• RDMA
• Terraform
• NodeJS
• DevOps

More:

We are Together AI, a research-driven artificial intelligence company focused on open and transparent AI systems that expand innovation and deliver better outcomes for society. Our mission is to significantly reduce the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets, and our team has helped drive advances such as FlashAttention, Hyena, FlexGen, and RedPajama. We offer competitive compensation, startup equity, health insurance, additional benefits, and flexibility for remote work. The US base salary range for this full-time role is $250,000 to $300,000 plus equity and benefits, with compensation determined by location, level, experience, skills, and role-related knowledge. We are an equal opportunity employer and welcome applicants from all backgrounds.

last updated 33 week of 2026