#7 - Senior Machine Learning Engineer - Databricks

Role overview Own deployment and day-to-day operation of machine learning products built on Databricks, keeping production workflows reliable, observable, and scalable across environments and countries. You’ll coordinate with development and platform teams to investigate incidents and maintain the pipeline from data generation through publishing results to operational users.

Responsibilities - Orchestrate Databricks Jobs and workflows, chaining tasks and handling success and failure conditions. - Configure and promote deployments across development, QA, and production using Databricks Asset Bundles, with deployment resources organized by country. - Manage model and artifact lifecycles in MLflow and Unity Catalog, including registration, versioning, champion/challenger aliases, and rollback. - Coordinate compute across workspaces, apply cost-monitoring tags, and integrate operational monitoring and AIOps practices. - Diagnose production incidents end to end and coordinate resolution with development squads.

Requirements - Demonstrated experience operating data or ML pipelines on Databricks, including Jobs, Workflows, and cluster policies. - Strong CI/CD experience, including Azure DevOps, Git workflows, and pull requests. - Experience with infrastructure as code using Databricks Asset Bundles and code quality tools such as black, isort, and mypy. - Advanced Python and SQL skills, plus experience with Delta and Unity Catalog. - Strong operational ownership and ability to troubleshoot production systems across environments.

Nice to have - Experience with multi-country schemas, drift or cost monitoring, and deployment automation. - Background developing AI agents or agent infrastructure, such as agent orchestration or MCP. - Based in Mexico or a time zone with substantial overlap with Mexico working hours.

Benefits and work setup The role is remote-first. Listed benefits include covered certifications across several cloud and data platforms, a birthday day off plus an additional vacation week, referral bonuses, monthly benefits-marketplace credits, and an annual team trip.