MLOps / DevOps Engineer – AI Infrastructure

CreatorIQ • New York, NY

1d • $121,000 - $155,000

About The Position

CreatorIQ is seeking an MLOps / DevOps Engineer to support and improve its cloud and ML/AI infrastructure, automate deployments, and maintain CI/CD pipelines for efficient, secure, and scalable development workflows. The role contributes to infrastructure automation, monitoring, cloud security, and high availability, and works with Software and ML Engineers, Product Support, QA, and Security teams.

The engineer will manage cloud environments, CI/CD pipelines, and Infrastructure as Code; support infrastructure for AI and agentic products; operate ML platform infrastructure such as Databricks and SageMaker; and maintain production model-serving systems. The position also covers observability, incident response, troubleshooting, documentation, and collaboration with international teams across time zones.

CreatorIQ uses a flexible work model that combines in-person and remote work.

Requirements

• At least 3 years of experience in DevOps, Cloud Engineering, Site Reliability Engineering, or a similar infrastructure-focused role.
• At least 2 years of hands-on experience supporting production ML/AI infrastructure, including model serving, training pipelines, and model monitoring.
• At least 2 years of hands-on experience with Databricks (clusters, jobs, ML pipelines, or Model Serving) and/or AWS SageMaker (endpoints, inference, model deployment, provisioned throughput, or autoscaling) in a production environment.
• At least 2 years of hands-on experience with AWS services such as EC2, S3, RDS, Lambda, IAM, VPC, SQS, or API Gateway, or similar services.
• At least 2 years of experience 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, and network security.
• Scripting experience with Python, Bash, or similar languages to automate infrastructure and operational tasks.

Nice To Haves

• Experience with Google Cloud, particularly in multi-cloud environments.
• Familiarity with Helm and service mesh technologies such as Istio, Linkerd, or Traefik.
• Experience designing serverless and event-driven architectures using AWS Lambda, API Gateway, and SQS beyond basic usage.
• 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, or Grafana.
• 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.

Responsibilities

• Support and maintain scalable, highly available, secure cloud infrastructure in accordance with company policies and standards.
• Provision and manage cloud resources using Infrastructure as Code tools such as Terraform, Terragrunt, and CloudFormation.
• Implement cloud security practices including access controls, encryption, vulnerability management, and secure infrastructure configurations.
• Support containerized environments and orchestration platforms, apply DevSecOps principles, and participate in disaster recovery planning, testing, and recovery.
• Maintain and optimize CI/CD pipelines for application and ML model deployments, improve deployment reliability, and support zero-downtime deployment strategies.
• Automate configuration management, infrastructure provisioning, and operational processes; develop scripts to reduce manual work.
• Troubleshoot deployment and pipeline issues and implement improvements to prevent recurrence.
• Help design, deploy, operate, and secure infrastructure for AI and agentic products, including MCP, agents, integrations, internal tooling, and customer-facing use cases.
• Use and evaluate AI-assisted engineering tools and workflows to improve DevOps productivity, infrastructure management, troubleshooting, and operational efficiency.
• 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, partnering with ML Engineering on evaluation, quality thresholds, and model correctness.
• Partner with ML Engineering to support reliable CI/CD and production deployment of ML models.
• Maintain monitoring, logging, metrics, and alerting solutions; improve observability through log aggregation, metrics collection, monitoring, and alerting.
• Support incident response and perform root cause analysis for infrastructure and deployment-related issues.
• Work 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 and provide technical infrastructure support when needed.
• Maintain accurate internal technical and operational documentation.
• Collaborate with international teams across multiple time zones.

Benefits

• 15 days of vacation, floating and company holidays, wellness benefits, and paid parental leave.
• Comprehensive medical, dental, vision, life, and disability insurance, plus additional wellness benefits.
• A 401(k) plan.
• A work-from-home stipend to assist with setting up a home office.
• Access to a learning platform and training tools.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed