Job description
We’re looking for a DevOps Engineer to help design, build, and optimize the cloud infrastructure powering our machine learning operations. You’ll play a key role in scaling AI models from research to production — ensuring smooth deployments, real-time monitoring, and rock-solid reliability across our Google Cloud Platform (GCP) environment.
You’ll work hand-in-hand with data scientists, ML engineers, and other DevOps experts to automate workflows, enhance performance, and keep our AI systems running seamlessly for millions of players worldwide.
What You’ll Do
Manage, configure, and automate cloud infrastructure using tools such asTerraformandAnsible.
ImplementCI/CD pipelinesfor ML models and data workflows, focusing on automation, versioning, rollback, and monitoring with tools likeVertex AI,Jenkins, andDataDog.
Build and maintain scalabledata and feature pipelinesfor both real-time and batch processing usingBigQuery,BigTable,Dataflow,Composer,Pub/Sub, andCloud Run.
Set up infrastructure formodel monitoringand observability — detecting drift, bias, and performance issues usingVertex AI Model Monitoringand custom dashboards.
Optimizeinference performance, improving latency and cost-efficiency of AI workloads.
Ensure overallsystem reliability, scalability, and performanceacross the ML/Data platform.
Define and implementinfrastructure best practicesfor deployment, monitoring, logging, and security.
Troubleshoot complex issues affecting ML/Data pipelines and production systems.
Ensure compliance withdata governance, security, and regulatory standards, especially for real-money gaming environments.
What We’re Looking For
3+ yearsof experience as a DevOps Engineer, ideally with a focus on ML and Data infrastructure.
Strong hands-on experience withGoogle Cloud Platform (GCP)— especiallyBigQuery,Dataflow,Vertex AI,Cloud Run, andPub/Sub.
Proficiency withTerraform(and bonus points forAnsible).
Solid grasp ofcontainerization(Docker, Kubernetes) and orchestration platforms likeGKE.
Experience building and maintainingCI/CD pipelines, preferably withJenkins.
Strong understanding ofmonitoring and logging best practicesfor cloud and data systems.
Scripting experience withPython,Groovy, orShell.
Familiarity withAI orchestration frameworks(LangGraph or LangChain) is a plus.
Bonus points if you’ve worked ingaming,real-time fraud detection, orAI-driven personalization systems.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.