MLOps / DevOps Engineer – AI Infrastructure

The DevOps Engineer is responsible for supporting and improving cloud and ML/AI infrastructure, automating deployments, and maintaining CI/CD pipelines to ensure efficient, secure, and scalable development workflows. This role plays a crucial part in infrastructure automation, monitoring, and cloud security while collaborating with Software and ML Engineers, Product support, QA, and Security teams.
As a key member of the DevOps team, the DevOps Engineer helps manage cloud environments, CI/CD pipelines, and Infrastructure as Code (IaC), ensuring high availability and compliance with security best practices.

In this role, you’ll get to:

Cloud Infrastructure, Security & Reliability

• Support and maintain scalable, highly available, and secure cloud infrastructure in accordance with company policies and standards.

• Provision and manage cloud resources using Infrastructure as Code (Terraform, Terragrunt, CloudFormation).

• Implement cloud security best practices, including IAM/role-based access controls, encryption, vulnerability management, and secure infrastructure configurations.

• Support containerized environments and orchestration platforms.

• Apply DevSecOps principles across infrastructure and deployment workflows.

• Participate in disaster recovery planning, testing, and recovery activities.

CI/CD, Automation & Deployment

• Maintain and optimize CI/CD pipelines using tools such as GitLab CI/CD and Jenkins, supporting application and ML model deployments.

• Improve deployment reliability and support zero-downtime deployment strategies.

• Automate configuration management, infrastructure provisioning, and routine operational processes.

• Troubleshoot deployment and pipeline issues and implement improvements to prevent recurrence.

• Develop scripts and automation to reduce manual work and improve engineering efficiency.

AI & Agentic Infrastructure

• Help design, deploy, operate, and secure infrastructure supporting AI and agentic products, including MCP, agents, integrations, internal tooling, and customer-facing use cases.

• Use AI-assisted engineering tools, coding copilots, and AI-driven troubleshooting to improve DevOps productivity and reduce repetitive operational work.

• Evaluate and adopt practical AI-enabled workflows that improve infrastructure management, troubleshooting, and operational efficiency.

MLOps & ML Platform Infrastructure

• Operate and scale ML platform infrastructure, including Databricks and Sagemaker clusters, jobs compute, ML pipelines, and Model Serving endpoints.

• Manage production model-serving infrastructure, including compute capacity, provisioned throughput, and autoscaling for high-throughput inference workloads.

• Maintain infrastructure-level monitoring for model drift, data quality, inference performance, and serving health, while partnering with ML Engineering on model evaluation, quality thresholds, and model correctness.

• Partner with ML Engineering to support reliable CI/CD and production deployment of ML models.

Observability, Incident Response & Engineering Collaboration

• Maintain monitoring, logging, metrics, and alerting solutions using tools such as Prometheus, Grafana, Coralogix, and CloudWatch.

• Support incident response and perform Root Cause Analysis (RCA) for infrastructure and deployment-related issues.

• Improve system observability through effective log aggregation, metrics collection, monitoring, and alerting.

• Partner with Software Engineers, ML Engineers, QA, and Software Engineers in Test to improve deployment workflows and integrate automated testing into CI/CD pipelines.

• Collaborate with IT Security to maintain secure cloud operations and infrastructure policies.

• Respond to engineering and Product Support requests in a timely manner and provide technical infrastructure support when needed.

• Maintain accurate internal technical and operational documentation.

• Collaborate effectively with international teams across multiple time zones

Who you are and what you’ll need for this position:

• 3+ years of experience in DevOps, Cloud Engineering, Site Reliability Engineering (SRE), or a similar infrastructure-focused role.

• 2+ years of hands-on experience supporting production ML/AI infrastructure, including model serving, training pipelines, and model monitoring.

• 2+ Hands-on experience with Databricks (clusters, jobs, ML pipelines, Model Serving) and/or AWS SageMaker (endpoints, inference, model deployment, provisioned throughput, autoscaling) in a production environment.

• 2+ years of hands-on experience with AWS services such as EC2, S3, RDS, Lambda, IAM, VPC, SQS, API Gateway, or similar services.

• 2+ years of experience working with containerized environments and orchestration platforms such as Kubernetes and Amazon EKS.

• Strong experience building and maintaining CI/CD pipelines using tools such as GitLab CI/CD or Jenkins.

• Hands-on experience with Infrastructure as Code using Terraform, Terragrunt, CloudFormation, or similar technologies.

• Strong Linux system administration and troubleshooting skills.

• Solid understanding of networking fundamentals, including routing, load balancing, network security, and related concepts.

• Scripting experience with Python, Bash, or similar languages to automate infrastructure and operational tasks.

Nice to have:

• Experience with Google Cloud, particularly for candidates who have worked across multi-cloud environments.

• Familiarity with Helm and service mesh technologies such as Istio, Linkerd, Traefik, or similar tools.

• Experience designing serverless and event-driven architectures (beyond basic usage) using AWS Lambda, API Gateway, and SQS.

• Exposure to cloud and infrastructure security practices, including vulnerability management and tools such as Nessus, Prowler, Trivy, or firewalls.

• Knowledge of security standards, compliance requirements, and cloud security best practices.

• Experience with observability, log analysis, and monitoring platforms such as Coralogix, Prometheus, Grafana, or similar solutions.

• FinOps experience, including cloud cost monitoring, optimization, and accountability practices.

• Experience with API gateway or API management platforms such as Kong or Apigee.

• Hands-on experience using AI tools to improve engineering workflows, automation, troubleshooting, or agentic use cases.

Confidence can sometimes hold us back from applying for a job. But there's no such thing as a 'perfect' candidate. Have 50% of the criteria? Excited about this opportunity? Interested about what we do at CreatorIQ? Please apply!

• People: Work with talented, collaborative, and friendly people who love what they do.

• Guidance: Utilize our learning platform to fully get the training and tools you'll need to become successful here from your first day with us.

• Work/life harmony: 15 days of vacation, floating and company holidays, wellness benefits, and paid parental leave.

• Whole Health Package: Comprehensive medical, dental, vision, life, and disability insurance, plus additional wellness benefits.

• Planning for the future: A 401(k) plan to help you plan ahead.

• Work from home stipend: To assist you in setting up a home office that works for you.

We know that benefits play a significant role in your overall compensation. We invite you to review our benefits and perks.

Who we are:

CreatorIQ is enterprise infrastructure for creator marketing, trusted by more than 1,300 of the world's leading brands and agencies, including Beiersdorf, Delta Air Lines, Dentsu, Google, Nestlé, and Wella. Powered by the Creator Graph®, CreatorIQ's proprietary AI and intelligence foundation grounded in over 11 years of data, it’s built for teams, agents, and the entire enterprise tech stack. With headquarters in Los Angeles and offices in Austin, London, Manila, New York, San Francisco, and Warsaw, CreatorIQ’s global team moves quickly and deliberately because we're setting the pace for an industry that's still being defined.

Learn more at www.creatoriq.com and follow us on LinkedIn and Instagram.

At CreatorIQ, different perspectives make our work better. The people we hire come from different backgrounds and think in different ways — and that's exactly what helps us connect with each other, and with the customers and creators we serve.We are committed to fostering an inclusive, equitable, and empowering work environment where everyone can thrive, regardless of race, ethnicity, gender, sexual orientation, age, religion, disability, or any other characteristic that makes us unique. By embracing our core values of being intentional, pursuing excellence every day, embracing the journey together, and being a good human, we create an atmosphere that promotes collaboration and growth. Join us to celebrate differences, innovate together, and be a part of a business that is disrupting the marketing industry.

AI Transparency Notice

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications and note taking during interviews. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please refer to our Global Candidate Privacy Notice.