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Sr. AI/ML Engineer (MXC)

CompraTica Empleos

EMP:Technology
Mexico
Tiempo Completo
Remoto
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Descripción

Do work that matters.

    At AlertMedia, we help organizations protect their people, operations, and brand.

Our modern Risk Intelligence and Response platform empowers teams to detect emerging threats, assess impact, and respond with confidence.

We believe building resilience should be simpler—and it starts with bringing critical information and workflows together in one unified platform.

Our core values drive us in our important mission of keeping people safe & informed:   We’re humans not robots  Customers always come first  We work better together  Simplicity is our strength  Our reputation is priceless  Hard work pays off      AlertMedia is looking for an innovative and hands-on Sr.

AI/ML Engineer with a strong background in applied machine learning and data science to lead the evaluation, training, and integration of advanced AI and machine learning models across our product suite.

In this role, you will help shape our AI strategy by identifying the most appropriate models for our use cases, optimizing their performance through fine-tuning and prompt engineering, and ensuring their responsible deployment within our platforms.

You will have the opportunity to show who you are throughout our interview process; we don’t ask any trick questions or expect you to perform a whiteboard exercise.

We want to see you shine by showing us work you are most proud of!    Who you are:     You are an applied AI and machine learning engineer with strong data science fundamentals, deeply curious.

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what's possible with large language models and practical machine learning applications

You’re a collaborative engineer who thrives in a fast-moving environment, and you’re as comfortable training and fine-tuning models as you are crafting prompts or evaluating model outputs.

You have a strong understanding of ML fundamentals, but you're pragmatic in applying the right solution for the problem.

       What you get to do every day:  Train and fine-tune supervised learning models (e.

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