#2 - Senior Machine Learning Engineer - Databricks
Ciudad de Mexico
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingOrchestrate production pipelines on Databricks Jobs with chained tasks and failure handling
Configure and promote deployments via Databricks Asset Bundles across dev, qa and prd
Manage model and artifact lifecycle in MLflow and Unity Catalog, including rollback
Manage compute across workspaces and standardize cost-monitoring tags
Diagnose runtime incidents and coordinate fixes with development squads
From the employer’s posting
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
Manage the lifecycle of models and artifacts in MLflow + Unity Catalog (registration, versioning, Champion/Challenger aliases, rollback)
manage compute across workspaces, standardize cost-monitoring tags (FinOps)
Master the product end-to-end to diagnose runtime incidents and coordinate with development squads.
Tools in this posting
- Python
- SQL
- AWS
- Azure
- Databricks
- dbt
- MLflow
- GCP
Source — Tool mentions in context
- Solid CI/CD experience (Azure DevOps, gitflow, PRs), IaC with DABs, and code quality standards (black, isort, mypy). - Advanced Python, SQL, Delta / Unity Catalog. Nice to Have 😉
🌟 Our Partnerships - Amazon Web Services - Astronomer
- Remote-first culture – work from anywhere! 🌍 - AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered - Birthday off + an extra vacation week (Mutt Week! 🏖️)
- 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.
- Astronomer - Databricks 🌟 Our Values
Responsibilities 🤓 - 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.
- 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 (registration, versioning, Champion/Challenger aliases, rollback).
Required Skills 🚀 - 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).
- 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 (registration, versioning, Champion/Challenger aliases, rollback). - Ensure operational continuity: manage compute across workspaces, standardize cost-monitoring tags (FinOps), and integrate with AIOps/observability.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 8, 2026 · 19 days ago
- Recorded sightings
- 18
- Last seen by us
- Oct 28, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
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- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀
At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.
This opportunity is with a leading multinational beverage company based in Mexico City.
We are looking for a Machine Learning Engineer Senior to join our team 🐶🚀. You'll own the deployment, job configuration, and end-to-end operation of our AI Factory products, making sure the full pipeline — from data generation to publishing results to operations — runs reliably, observably, and scalably across countries.
This role works closely with development squads and platform teams, diagnosing runtime incidents and keeping production pipelines healthy across environments. Strong ownership, operational rigor, and end-to-end product knowledge are essential to succeed in this fast-paced, collaborative environment.
🚀 What We Do
- Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
- Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
- Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
- Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
- Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
- Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
- Amazon Web Services
- Astronomer
- Databricks
🌟 Our Values
Responsibilities 🤓
- 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 (registration, versioning, Champion/Challenger aliases, rollback).
- Ensure operational continuity: manage compute across workspaces, standardize cost-monitoring tags (FinOps), and integrate with AIOps/observability.
- Master the product end-to-end to diagnose runtime incidents and coordinate with development squads.
Required Skills 🚀
- 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.
Nice to Have 😉
- Experience with multi-country schemas, drift/cost monitoring, and deployment automation.
- Experience developing AI agents / agentic infrastructure (e.g. Mosaic AI Agent Framework, agent orchestration, MCP).
- Currently based in Mexico or a location within a similar time zone, allowing for strong overlap with Mexico working hours.
🎁 Perks
- 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 – help us grow the team & get rewarded!
- Maslow: Monthly credits to spend in our benefits marketplace.
- ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
Employment type
Remote - Latam
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Ciudad de Mexico
🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀 At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning. This opportunity is with a leading multinational beverage company based in Mexico City.
More source context
🎁 Perks - Remote-first culture – work from anywhere! 🌍 - AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
More relevant text appears in the full description.
- Work authorization
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