Roblox предлагает чётко очерченную senior-роль в инфраструктуре данных, работу с современными системами большого масштаба и зарплату на уровне рынка. Основные ограничения - требования к разрешению на работу в США и регулярное присутствие в офисе.
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Ограничения по визеСовременный стекДостойная зарплатаЧёткая зона ответственностиМасштабная платформаРабота в офисе
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Текст:
Hirify AI/Оригинал
TL;DR
Senior Software Engineer, Data Infrastructure Compute (Spark/Kubernetes): Building and operating Spark compute platform services on Kubernetes, including job submission, interactive notebook compute, EKS cluster automation, scheduling, and auto-tuning with an accent on reliability, scalability, and cost efficiency. Focus on designing multi-tenant infrastructure, validating cluster upgrades, optimizing Spark workloads, and evaluating emerging execution technologies through production-scale benchmarks.
Location: San Mateo, California, United States; office-based roles are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday.
Salary: $243,290–$295,250 USD annual base pay.
Company
Roblox builds tools and platform infrastructure for immersive digital experiences created by a global community of developers and creators.
What you will do
Design, build, and operate Spark job submission services, APIs, scheduling integrations, and internal Spark libraries.
Deliver interactive Spark through Spark Connect, including provisioning and management of EKS compute, workload isolation, resource limits, and cost controls.
Automate EKS cluster fleet management, including blue-green rollouts that validate AMIs and Kubernetes versions with minimal disruption.
Develop auto-tuning capabilities using Spark history and event logs to improve job performance and reduce compute cost.
Operate and upgrade YuniKorn-based batch scheduling with queue design, quotas, tenant fairness, and version management.
Define SLOs and observability, reduce incidents and operational toil, evaluate emerging technologies, and partner with data engineering, ML, analytics, and infrastructure teams.
Requirements
5+ years of experience building and operating production-grade distributed systems or infrastructure platforms.
Hands-on experience running Apache Spark on Kubernetes, including executor and driver behavior, resource tuning, and troubleshooting failed or slow jobs; platform-building experience is required.
Strong experience operating production Kubernetes clusters at scale, including upgrades, node lifecycle, autoscaling, and operators or controllers.
Strong proficiency in at least one of Go, Java, Scala, or Clojure, with experience writing clean, well-tested, maintainable backend code.
Experience with AWS, including EKS, EC2, IAM, and S3, or equivalent GCP services, plus infrastructure-as-code.
Experience taking systems from design through production operation, including on-call, incident response, and observability.
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.
For US-based roles, candidates must have US work authorization; certain US visa categories may not be supported.
Nice to have
Python experience for tuning and analysis tooling.
Experience with YuniKorn, Volcano, Kueue, or other Kubernetes batch schedulers.
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 building tooling with Spark event logs or metrics for tuning, cost attribution, or anomaly detection.
Experience maintaining internal Spark builds or leading Spark version upgrades.
Familiarity with native execution engines such as Comet, Gluten, or Velox, or with JVM performance tuning.
Experience migrating workloads from YARN/Hadoop to Kubernetes.
Open-source contributions in the data or Kubernetes ecosystem.
Experience operating at consumer-internet scale with 100M+ users.
Culture & Benefits
Work on large-scale systems supporting petabytes of daily data for analytics, machine learning, and product decisions.
Full-time employees are eligible for equity compensation and company benefits.
Work includes cross-functional collaboration with data engineering, ML, analytics, and infrastructure teams.
Roblox provides equal employment opportunities and reasonable accommodations during the recruiting process.
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