Remote ML Engineer: Build Production-Ready Models

BairesDev; United States; À distance; MXN 1 657 000 - 2 577 000; Plein temps

Avantages offerts par ce poste

100% remote

USD or local currency pay

Home office setup

Flexible hours

Parental leave

Holidays & vacations

Global team

Mentorship & growth

Résumé du poste

BairesDev, a global technology company, is hiring a Machine Learning Engineer for a fully remote role. You will design and deploy production ML pipelines, integrate data science with engineering, and ensure scalable model serving and monitoring.

We seek 4+ years of ML or software engineering, Python expertise, and experience with TensorFlow or PyTorch, plus strong English. 100% remote, USD or local currency pay, flexible hours, and a multicultural, mentorship-rich environment.

Qualifications

• 4+ years of experience in ML or software engineering.
• Proven ability to build and deploy ML models to production.
• Proficiency with Python and DL frameworks (TensorFlow, PyTorch).
• Experience with MLOps and model serving infrastructure.
• Strong knowledge of training, serving, and monitoring large-scale ML systems.
• Advanced English proficiency.

Responsabilités

• Design and develop production-ready ML pipelines.
• Deploy and manage scalable model serving infrastructure.
• Implement MLOps to automate testing, deployment, versioning.
• Monitor models for performance drift and reliability.
• Collaborate with data scientists to productionize models.

Connaissances

Machine Learning

Python

ML pipelines

MLOps practices

english proficiency

Outils

TensorFlow

PyTorch

Model serving infra

Description du poste

BairesDev, a global technology company, is hiring a Machine Learning Engineer for a fully remote role. You will design and deploy production ML pipelines, integrate data science with engineering, and ensure scalable model serving and monitoring.

We seek 4+ years of ML or software engineering, Python expertise, and experience with TensorFlow or PyTorch, plus strong English. 100% remote, USD or local currency pay, flexible hours, and a multicultural, mentorship-rich environment.