Senior Machine Learning Engineer

Bjak; Nuevo León; Presencial; MXN 1.429.081 - 1.786.352; Jornada completa

Descripción de la vacante

A leading AI technology firm in Mexico, Nuevo León is seeking a Senior Member of Technical Staff, Machine Learning to build and operate critical ML systems. The role involves independently owning projects, debugging production issues, and collaborating with teams to develop user-impacting solutions. Ideal candidates should have experience in ML system development and coding in Python, with an emphasis on production-ready systems. This hands-on role promises significant impact in the evolving field of AI.

Formación

• Experience building and shipping ML systems for real users.
• Understanding of how ML models behave in production environments.
• Ability to write well-structured production-quality code.

Responsabilidades

• Build ML systems for a proactive AI product.
• Owner of data preparation, training, and evaluation.
• Collaborate with cross-functional teams to develop impactful solutions.

Conocimientos

Building and shipping ML systems

Understanding behavior of ML models in production

Writing production-quality code

Ownership and independence

Fast learning and clear communication

Herramientas

Python

PyTorch

JAX

GPU-based training

Descripción del empleo

About the Role

A1 is building a proactive AI system that carries work forward across conversations, tools, and time.

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.

This is a hands‑on, high‑impact role focused on depth.

Focus

• 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

Ideal Experience

• 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.

Outcomes

• 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.

How We Work

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.

Interview process

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.

Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.

We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.