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DevOps Engineer – ML & Data Infrastructure
High 5 GamesDevOps Engineer responsible for building and optimizing cloud infrastructure for machine learning operations in gaming. Collaborating with data scientists and ML engineers to ensure reliability and performance.
Tech Stack
Tools & technologiesAnsibleBigQueryCloudDockerGoogle Cloud PlatformGroovyJenkinsKubernetesPythonTerraform
About the role
Key responsibilities & impact- Manage, configure, and automate cloud infrastructure using tools such as Terraform and Ansible.
- Implement CI/CD pipelines for ML models and data workflows, focusing on automation, versioning, rollback, and monitoring with tools like Vertex AI, Jenkins, and DataDog.
- Build and maintain scalable data and feature pipelines for both real-time and batch processing using BigQuery, BigTable, Dataflow, Composer, Pub/Sub, and Cloud Run.
- Set up infrastructure for model monitoring and observability — detecting drift, bias, and performance issues using Vertex AI Model Monitoring and custom dashboards.
- Optimize inference performance, improving latency and cost-efficiency of AI workloads.
- Ensure overall system reliability, scalability, and performance across the ML/Data platform.
- Define and implement infrastructure best practices for deployment, monitoring, logging, and security.
- Troubleshoot complex issues affecting ML/Data pipelines and production systems.
- Ensure compliance with data governance, security, and regulatory standards, especially for real-money gaming environments.
- Lead and mentor DevOps engineers, helping guide technical decisions and operational processes.
- Support sprint planning, task prioritization, and cross-functional coordination across infrastructure and platform initiatives.
- Conduct code reviews, share best practices, and contribute to building a high-performing engineering culture.
- Collaborate closely with ML, Data, Product, and Security teams to align infrastructure strategy with business objectives.
Requirements
What you’ll need- 5+ years of experience as a DevOps Engineer, ideally with a focus on ML and Data infrastructure.
- Experience leading projects, mentoring engineers, or managing technical teams.
- Strong hands-on experience with Google Cloud Platform (GCP) — especially BigQuery, Dataflow, Vertex AI, Cloud Run, and Pub/Sub.
- Proficiency with Terraform (and bonus points for Ansible).
- Solid grasp of containerization (Docker, Kubernetes) and orchestration platforms like GKE.
- Experience building and maintaining CI/CD pipelines, preferably with Jenkins.
- Strong understanding of monitoring and logging best practices for cloud and data systems.
- Scripting experience with Python, Groovy, or Shell.
- Familiarity with AI orchestration frameworks (LangGraph or LangChain) is a plus.
- Strong communication, collaboration, and stakeholder management skills.
- Bonus points if you’ve worked in gaming, real-time fraud detection, or AI-driven personalization systems.
Benefits
Comp & perks- Health insurance
- Retirement plans
- Paid time off
- Remote work options
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
TerraformAnsibleCI/CD pipelinesBigQueryDataflowVertex AICloud RunDockerKubernetesPython
Soft Skills
leadershipmentoringcommunicationcollaborationstakeholder management