Design and maintain robust ML deployment pipelines to ensure seamless model delivery.
Automate model training, deployment, and monitoring workflows to increase operational efficiency.
Collaborate closely with Data Scientists and Engineering teams to integrate models into production environments.
Optimize cloud-based infrastructure to enhance the scalability and reliability of ML systems.
Implement CI/CD best practices specifically tailored for machine learning lifecycles.
Monitor production systems and proactively troubleshoot performance or governance issues.

Residency and work authorization in Mexico. (Any city)
Extensive experience as an MLOps Engineer or Machine Learning Engineer within production environments.
Advanced proficiency in Python.
Proven track record deploying, monitoring, and maintaining ML models at scale.
Hands-on experience with Docker and Kubernetes for containerization and orchestration.
Strong expertise in cloud platforms such as AWS, Azure, or GCP.
Deep understanding of model governance and the end-to-end ML lifecycle.
Experience with CI/CD pipelines for machine learning workflows is required.
Proficiency with ML orchestration tools such as Kubeflow, Airflow, or MLFlow is highly preferred.
Experience with Infrastructure as Code (IaC) using Terraform is preferred.
Familiarity with monitoring and observability tools in a distributed environment is a plus.
Experience with LLMOps or GenAI pipelines is a significant plus.
Background working with enterprise-scale infrastructure or within regulated, high-compliance environments is a plus.
Familiarity with managed platforms like Databricks, SageMaker, or Vertex AI is preferred.

100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection.
Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.
Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed.
Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.
Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.

Senior MLOps Engineer – Digital Transformation

Key skills