Orchestrate production pipelines on Databricks and manage model lifecycles using MLflow and Unity Catalog. Ensure operational continuity by managing compute resources, cost-monitoring tags, and coordinating with development squads.
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 to join our team and work on high-impact projects for a major multinational beverage company based in Mexico πΆπ.
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π 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.
π Our Partnerships
Amazon Web Services
Astronomer
Databricks
π Our Values
π We are Data Nerds
π€ We are Open Team Players
π We Take Ownership
π We Have a Positive Mindset
π Curious about what weβre up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects weβre working on! π
Responsibilities π€
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 β qa β 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.
“I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!”