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WekaIO

AI-native data platform for high-performance workloads

Data Platform Administrator

Database AdministrationConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • At least 10 years of experience administering enterprise infrastructure at scale, with strong file, object, or block storage experience.
  • Deep Linux administration skills, including RHEL-family and Ubuntu, in distributed environments.
  • Hands-on experience with high-speed networking, including Ethernet, InfiniBand, RDMA, DNS, ACLs, and TCP/IP fundamentals.
  • Working knowledge of Kubernetes and containers, including persistent storage, CSI, and operators.
  • Experience operating GPU, HPC, or large cloud infrastructure for external customers or multiple tenants.
  • Experience with at least one major cloud: AWS, Azure, Google Cloud, or Oracle Cloud.
  • Proficiency in Python, Bash, or Ansible.
  • Experience with monitoring and alerting stacks, including Prometheus, Grafana, and log and metrics tooling.
  • Experience with ticketing systems such as Jira and discipline in major incident management.
  • Ability to explain changes to engineers and executives through clear written and verbal communication.
  • Strong technical writing skills, including creating runbooks usable by someone unfamiliar with the environment.

Responsibilities

  • Run the WEKA environment day to day, including monitoring, health, upgrades, capacity, configuration, and audits.
  • Create and manage file systems, tiering to object storage, snapshots, quotas, and protocol configuration (POSIX, NFS, SMB, S3) as tenants onboard and grow.
  • Own the operational run state by keeping the environment healthy, documented, and recoverable.
  • Execute approved changes by confirming scope and approval, classifying risk, validating, maintaining a rollback, and recording the outcome.
  • Watch for drift, capacity pressure, and anomalies, and raise them early with a recommended path.
  • Work with customer tenants and platform teams to understand workload storage use across training, inference, checkpointing, data loading, and scheduling, as needed.
  • Tune WEKA to fit workloads, including filesystem layout, tiering, snapshot policy, quotas, and per-tenant QoS.
  • Validate and standardize the client layer, including GPU node clients, BlueField-3 and SR-IOV networking, mount options, cgroups and kubelet CPU policy, and the WEKA Kubernetes operator and CSI driver.
  • Onboard new tenants and clients using a repeatable, verified procedure; check configurations and scripts before production.
  • Establish performance baselines, run benchmarks and tests with tenants, and report what changed and why.
  • Identify scaling limits in advance, including client counts, process ceilings, and NAT and routing behavior across tenant networks.
  • Build and maintain customer operating runbooks with procedures, access guidance, validation, rollback, and recovery steps.
  • Turn repeated manual work into scripts, automation, or checklists using Python, Bash, and Ansible.
  • Prepare handovers and backup briefs before time off or coverage changes.
  • Explain procedures and decisions to customer operators so they become more capable and less dependent.
  • Open and update cases with the observed condition, customer impact, completed work, evidence, and requested next step; follow the established path to Technical Services, GRE, and R&D.
  • Keep the extended WEKA team informed of changes, risks, and customer communications.
  • Work with cloud providers, network teams, and other third parties in the customer’s environment to resolve issues.
  • Contribute operational results, trends, and risks to weekly status and quarterly reviews.

Desired Qualifications

  • Prior experience with WEKA or another parallel or distributed file system.
  • Experience running Slurm or Kubernetes-based AI/ML platforms.
  • Experience with NVIDIA GPU cluster networking and DGX-class systems.
  • Experience collaborating between support and product or engineering teams.
  • Familiarity with Confluence, Slack, and other collaboration tools.

About the Company

WekaIO

AI-native data platform for high-performance workloads

WEKA is an AI-native data platform that provides a cloud- and hardware-agnostic software solution for performance-heavy AI, ML, and GPU workloads. The WEKA Data Platform organizes and speeds data across on-premises, cloud, edge, and hybrid environments to turn isolated data into dynamic pipelines. It delivers high throughput and scalable data management to support enterprise AI initiatives and research workloads, helping teams gain faster insights. WEKA differentiates itself with a single scalable platform that works across multiple infrastructure footprints and emphasizes energy efficiency, aiming to simplify and accelerate data-driven AI workflows for large enterprises and research groups while replacing legacy data silos.

Company size
501-1,000
Company stage
Series E
Total funding
$465.1M
Headquarters
Campbell, CA
Founded
2013

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