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.