Senior Machine Learning Engineer – Databricks

• Orchestrate production pipelines on Databricks Jobs, chaining tasks via depends_on and managing failure modes (ALL_SUCCESS / ALL_DONE)
• Configure and maintain deployments via Databricks Asset Bundles (DABs), promoting across dev → qa → prd targets, with resource/deployment files per country
• Manage the lifecycle of models and artifacts in MLflow + Unity Catalog, including registration, versioning, Champion/Challenger aliases, and rollback
• Manage compute across workspaces
• Standardize cost-monitoring tags (FinOps)
• Integrate with AIOps/observability
• Master the product end-to-end to diagnose runtime incidents
• Coordinate with development squads and platform teams
• Keep production pipelines healthy across environments

• Proven experience orchestrating data/ML pipelines on Databricks (Jobs, Workflows, cluster policies)
• Solid CI/CD experience (Azure DevOps, gitflow, PRs)
• Infrastructure as code with Databricks Asset Bundles (DABs)
• Code quality standards: black, isort, mypy
• Advanced Python, SQL, Delta / Unity Catalog
• Experience working with Large Language Models (LLMs) is nice to have
• Knowledge of AI agents and agentic systems is nice to have
• Familiarity with MLOps practices and tools is nice to have
• Experience deploying and maintaining Data Science and AI solutions in production environments is nice to have
• Knowledge of job orchestration, computing infrastructure, deployments, monitoring, and maintenance is nice to have
• Experience working with event data, user tracking, and application tagging is nice to have
• Ability to collaborate effectively with Product, Engineering, and Business teams is nice to have

• Remote-first culture – work from anywhere
• AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
• Birthday off + an extra vacation week (Mutt Week!)
• Referral bonuses
• Maslow: Monthly credits to spend in our benefits marketplace
• Annual Mutters' Trip – an unforgettable getaway with the team