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# Machine Learning Engineer

- **Company:** Ai-native
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Data Cleansing, Software Debugging, Python (Programming Language), Machine Learning, Pytorch, Low Latency, Production Code, Machine Learning Operations, Data Pipelines
- **Published:** July 22, 2026
- **Apply:** https://www.jobleads.com/es/job/ebbf909952bdc07183f55b62ba948e918

## About the Role

* You have built and shipped ML systems used by real users.
 * You understand how modern ML models behave - and misbehave - in production.
 * You write strong, production-quality code and think in systems, not scripts.
 * You take ownership, work independently, and push work across the finish line.
 * You learn fast, communicate clearly, and improve through iteration.

## Description

As a Senior Member of Technical Staff, Machine Learning, you are an independent owner of critical ML subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale., * Build core ML systems that power a proactive, long-horizon AI product.

 * Own work end-to-end: data preparation, training, evaluation, inference, and iteration.
 * Turn research ideas into working systems that run reliably in production.
 * Debug model failures and system issues using real production signals.
 * Iterate quickly: ship, measure outcomes, refine, and repeat.
 * Collaborate closely with research, product, and engineering to deliver real user impact.
 * Mentor and review work from other ML engineers through example and technical judgment.
 * Work under real production constraints: latency, cost, reliability, and safety

Tech Stack

 * Python
 * PyTorch / JAX
 * GPU-based training and inference systems, * ML models and systems in production consistently meet accuracy, latency, reliability, and efficiency targets.
 * Complex production issues are monitored, debugged, and resolved with minimal disruption.
 * Training, inference, and data pipelines are robust, scalable, and maintainable over time.
 * Drives measurable improvements in ML systems based on real-world signals and user feedback.
 * Provides mentorship and technical guidance to peers, raising the overall ML engineering standard.
 * Collaborates cross-functionally to ensure ML features integrate seamlessly into products and meet business goals., The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product


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