🚀 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.
- 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.
- 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.
