Senior ML Engineer — Remote, Deploy & Scale AI Pipelines

Muttdata; Ciudad de México; Remote; MXN 900,000 - 1,500,000; Full time

Benefits offered by this job

Remote-first culture

Certifications covered

Birthday off

Referral bonuses

Benefits marketplace credits

Annual team trip

Job summary

Muttdata, a remote-first data products startup, seeks a Senior Machine Learning Engineer to own end-to-end AI Factory deployments from data generation to publication in production. You will work with cross-country teams to keep pipelines reliable across environments.

Responsibilities include building and stabilizing Databricks pipelines, managing models with MLflow, and ensuring observability and cost efficiency. A strong ownership mindset is essential in a fast-paced, collaborative setting.

Qualifications

• Proven experience orchestrating data/ML pipelines on Databricks (Jobs, Workflows, cluster policies).
• Solid CI/CD experience (Azure DevOps, gitflow, PRs), IaC with DABs, and code quality standards (black, isort, mypy).
• Advanced Python, SQL, Delta / Unity Catalog.

Responsibilities

• Orchestrate production pipelines on Databricks Jobs and manage dependencies and failure modes.
• Configure and maintain deployments via Databricks Asset Bundles across dev → qa → prod with country-specific targets.
• Manage model/artifact lifecycles in MLflow and Unity Catalog including versioning and rollbacks.
• Ensure operational continuity by managing compute across workspaces, cost-monitoring, and observability integration.
• Diagnose runtime incidents and coordinate with development squads to keep pipelines healthy.

Skills

Databricks orchestration

CI/CD with IaC

Python & SQL

Tools

Databricks

MLflow

Unity Catalog

Job description

Muttdata, a remote-first data products startup, seeks a Senior Machine Learning Engineer to own end-to-end AI Factory deployments from data generation to publication in production. You will work with cross-country teams to keep pipelines reliable across environments.

Responsibilities include building and stabilizing Databricks pipelines, managing models with MLflow, and ensuring observability and cost efficiency. A strong ownership mindset is essential in a fast-paced, collaborative setting.