C
Jr AI/MLOps Engineer - USA
CirrusLabs
Location not stated
Remote
Junior
9 months ago
- AI/ML
- Machine Learning
- AI
- Azure
- AWS
- GCP
- CI/CD
- Docker
- Kubernetes
- IaC
- Secrets Management
- Devops
- GitHub Actions
- GitLab CI
- Jenkins
- Azure DevOps
- Git
- ECS
- Prometheus
- Grafana
- CloudWatch
- Datadog
- Python
- Bash
- MLflow
- Kubeflow
- Vertex AI
9 months ago
You have an entrepreneurial spirit. You enjoy working as a part of well-knit teams. You value the team over the individual. You welcome diversity at work and within the greater community. You aren't afraid to take risks. You appreciate a growth path with your leadership team that journeys how you can grow inside and outside of the organization. You thrive upon continuing education programs that your company sponsors to strengthen your skills and for you to become a thought leader ahead of the industry curve.
You are excited about creating change because your skills can help the greater good of every customer, industry and community. We are hiring a talented<Job Title>to join our team. If you're excited to be part of a winning team, CirrusLabs (http://www.cirruslabs.io) is a great place to grow your career.
Role Overview
The Junior AI/ML Ops Engineer will support the deployment and operation of machine learning models and AI agents in cloud environments such as Azure, AWS, and GCP. Working under the guidance of senior team members, this role focuses on CI/CD, observability, drift monitoring, model tracking, and infrastructure automation to ensure production-grade, stable, and compliant AI solutions.
Key Responsibilities
- Deploy and update ML models and AI agents on public cloud platforms (Azure, AWS, GCP), following guidance and standards from senior engineers.
- Implement and maintain CI/CD pipelines for model and agent deployment, including automated testing and safe rollout/rollback procedures.
- Set up and operate observability for AI workloads, including logging, metrics, alerts, and dashboards to monitor performance, latency, and availability.
- Configure and monitor model tracking, data/model drift alerts, and basic retraining triggers in collaboration with data science teams.
- Manage containerization and orchestration for AI services (e.g., Docker, Kubernetes), including GPU-aware configurations and autoscaling where needed.
- Contribute to infrastructure-as-code and automation scripts to provision and manage cloud resources reliably and repeatably.
- Help ensure deployments meet security, compliance, and reliability standards, including access control, secrets management, and auditability.
- Troubleshoot deployment, performance, and environment issues, escalating to senior engineers when appropriate.
Required Skills & Experience
- 1–3 years of experience in DevOps, ML Ops, or cloud engineering, or relevant internships/projects supporting ML systems in production.
- Basic experience deploying applications on at least one major cloud provider (Azure, AWS, or GCP).
- Familiarity with CI/CD tools (e.g., GitHub Actions, GitLab CI, Jenkins, Azure DevOps) and version control (Git).
- Understanding of containerization (Docker) and exposure to orchestration platforms (e.g., Kubernetes, ECS).
- Exposure to monitoring/observability tools (e.g., Prometheus, Grafana, CloudWatch, Datadog, or equivalent).
- Scripting/programming skills in Python, Bash, or similar for automation tasks.
- Strong problem-solving mindset, willingness to learn from senior team members, and ability to work in a collaborative engineering environment.
Nice-to-Have Skills
- Experience with GPU workloads, autoscaling, or distributed training/serving environments.
- Familiarity with ML-specific tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or similar platforms.
- Knowledge of model performance monitoring, data/model drift concepts, and basic ML lifecycle understanding.
- Any cloud associate-level certification (AWS, Azure, or GCP).
Jr AI/MLOps Engineer - USA · CirrusLabs