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Senior Software Engineer (Data Infrastructure Compute)

Roblox

Skills

Required

  • Spark
  • Kubernetes
  • tuning
  • EKS
  • Apache
  • GKE
  • troubleshooting
  • Go / Java / Scala / Clojure
  • backend
  • Python
  • EC2
  • S3
  • Karpenter / Helm / Terraform / Argo

Preferred

  • native execution engines
  • Comet
  • Gluten
  • Velox
  • JVM performance tuning
  • migrating workloads
  • YARN / Hadoop
  • upgrades
  • node lifecycle
  • autoscaling

Join Roblox as a Senior Software Engineer on the Data Platform Compute team. You will build and operate core compute platform services, launch interactive Spark at scale, run a safe automated cluster fleet, and shape the future of technology adoption at Roblox. You should have strong experience with Kubernetes, Spark on Kubernetes, and a background in building and operating production-grade distributed systems.

USD 243,290 - 295,250

Responsibilities

  • Concevoir, construire et exploiter le logiciel derrière la soumission de travaux Spark, y compris les API, l'intégration de la planification et les bibliothèques.
  • Lancer Spark interactif à grande échelle : livrer Spark Connect pour prendre en charge les flux de travail des notebooks.
  • Développer notre auto-tuner, qui analyse l'historique de Spark et les journaux d'événements pour recommander ou appliquer des modifications de configuration.
  • Kubernetes depth: Strong experience operating production Kubernetes clusters at scale, such as upgrades, node lifecycle, autoscaling, and operators or controllers

Requirements

  • Spark on Kubernetes: Hands-on experience running Apache Spark on Kubernetes (EKS, GKE, or self-managed) as a platform, including executor and driver behavior, resource tuning, and troubleshooting failed or slow jobs. We are looking for platform builders, not just Spark users
  • Engineering foundations: Strong proficiency in at least one of Go, Java, Scala, or Clojure, with a track record of writing clean, well-tested, maintainable backend code. Python is a plus, since much of our tuning and analysis tooling uses it
  • Technical leadership: Ability to influence design decisions across teams, mentor engineers, and drive alignment on cross-cutting changes

B.S. in Computer Science or equivalent practical experience

  • 5+ years of experience building and operating production-grade distributed systems or infrastructure platforms
  • Cloud fluency: Experience with AWS (EKS, EC2, IAM, S3) or GCP equivalents, and infrastructure-as-code
  • Operational ownership: Experience taking a system from design through production operation, including on-call, incident response, and observability
  • Experience with YuniKorn, Volcano, Kueue, or other batch schedulers on Kubernetes
  • Experience with Spark Connect, Livy, Kyuubi, or other interactive and gateway layers for Spark
  • Experience with the Spark Operator, Karpenter, Helm, Terraform, or Argo
  • Experience maintaining internal Spark builds or driving Spark version upgrades
  • Experience building tooling that uses Spark event logs or metrics for tuning, cost attribution, or anomaly detection
  • Experience operating at consumer-internet scale (100M+ users)

Preferred

  • Familiarity with native execution engines (Comet, Gluten, Velox) or JVM performance tuning
  • Experience migrating workloads from YARN/Hadoop to Kubernetes

Benefits

  • Contributions to open-source projects in the data or Kubernetes ecosystem

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