DevOps Engineer

High 5 Games; New York, Northern (NY, KY); Hybrid; USD 120,000 - 155,000; Full time

Job summary

High 5 Games seeks a DevOps Engineer to design and scale cloud infrastructure powering ML operations in Google Cloud Platform. You will collaborate with data scientists and ML engineers to automate workflows, deploy models, and monitor systems across a real-time gaming environment.

The role emphasizes reliability, security, and cost optimization, with opportunities to shape production ML platforms and enable scalable AI from research to live services.

Qualifications

• 3+ years of DevOps experience in ML or data infrastructure.
• Strong hands-on GCP experience with BigQuery, Dataflow, Vertex AI, Pub/Sub, and Cloud Run.
• Proficient in Terraform and Ansible for cloud provisioning.
• Containerization with Docker and Kubernetes (GKE).
• Experience building CI/CD pipelines, preferably Jenkins.
• Monitoring/logging for cloud/data systems (DataDog).
• Scripting in Python, Groovy, or Shell.
• Familiarity with AI orchestration frameworks (LangGraph/LangChain) is a plus.

Responsibilities

• Design, build, and optimize cloud infrastructure for ML operations.
• Develop CI/CD pipelines for ML models and data workflows.
• Build scalable data pipelines using BigQuery, Dataflow, and Pub/Sub.
• Set up model monitoring and observability with Vertex AI monitoring and dashboards.
• Optimize inference performance and cost-efficiency of AI workloads.
• Ensure reliability, scalability, and performance of the ML/Data platform.
• Define infrastructure best practices for deployment, monitoring, logging, and security.
• Troubleshoot complex issues in ML/Data pipelines and production systems.
• Ensure compliance with data governance and regulatory standards.

Skills

GCP

Terraform

Ansible

Docker

Kubernetes

Jenkins

CI/CD pipelines

Python/Shell/Groovy

DataDog

Vertex AI

BigQuery

Pub/Sub

Cloud Run

Tools

DataDog

Vertex AI

Pub/Sub

Cloud Run

BigQuery

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 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.

What We’re Looking For

• 3+ years of experience as a DevOps Engineer, ideally with a focus on ML and Data infrastructure.
• 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.
• Bonus points if you’ve worked in gaming, real‑time fraud detection, or AI‑driven personalization systems.