Key skills
AWSCloudDockerETLKubernetesPythonMLLLMMLOpsGitHub ActionsECSGitHubCI/CDRemote Work
About this role
Role Overview
- Own the full ML lifecycle
- Build and optimize CI/CD pipelines
- Design, deploy, and manage cloud infrastructure
- Automate deployment and orchestration
- Develop and deploy LLM workflows
- Ensure reliability and scalability of production systems
- Collaborate across teams to deliver ML-powered features
- Troubleshoot and resolve issues
- Document and standardize workflows
Requirements
- 5+ years in MLOps, DevOps, or infrastructure-focused engineering roles
- Strong proficiency in Python
- Hands-on experience with AWS, including ECS
- Expertise with Docker, Kubernetes
- Experience with GitHub Actions, and monitoring tools
- Familiarity with ML platforms, workflow orchestration
- Hands-on experience with LLM workflows
- Knowledge of ETL pipelines and observability best practices
- Ability to work with cross-functional teams
Tech Stack
- AWS
- Cloud
- Docker
- ETL
- Kubernetes
- Python
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options