Related skills
azure docker aws python kubernetes📋 Description
- Design and maintain ML deployment pipelines
- Automate training, deployment, and monitoring workflows
- Collaborate with data scientists and engineers to productionize models
- Optimize cloud infrastructure for scalable ML systems
- Implement CI/CD for ML lifecycles
- Monitor production systems and troubleshoot issues
🎯 Requirements
- Residency and work authorization in Mexico (Any city)
- Extensive experience as an MLOps Engineer or ML Engineer in production
- Advanced proficiency in Python
- Hands-on experience with Docker and Kubernetes
- Strong expertise in AWS, Azure, or GCP
- Experience with CI/CD pipelines for ML workflows
🎁 Benefits
- 100% remote work from any location
- Competitive USD pay
- Paid time off
- Work with autonomy
- Work with top American companies
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