Remote Deep Learning Engineer — Flexible Hours & Impact

BairesDev; México; Remote; MXN 1,282,000 - 2,015,000; Full time

Benefits offered by this job

100% remote work

USD or local currency compensation

Hardware and software setup

Flexible hours

Paid parental leaves

Promotions and growth opportunities

Job summary

BairesDev is seeking a Deep Learning Engineer to design and implement advanced neural network architectures, bridging research and production-grade software. You will optimize models for performance and scalability in a fully remote setting.

The role emphasizes PyTorch and Python, distributed training, GPU optimization, and end-to-end pipelines from data preprocessing to deployment, with a global, Top 1% talent culture and flexible hours.

Qualifications

• Proven expertise in PyTorch and designing custom model architectures.
• Hands-on experience with distributed training strategies and GPU optimization.
• Proficiency in implementing mixed-precision training techniques.
• Strong background in Python and large-scale model training pipelines.
• Advanced proficiency in English.

Responsibilities

• Design, develop, and implement custom deep learning model architectures using PyTorch and Python.
• Optimize training processes through distributed training and mixed-precision techniques to handle large-scale datasets.
• Enhance model performance by implementing GPU acceleration and memory-efficient training strategies.
• Build and maintain end-to-end deep learning pipelines, from data preprocessing to model deployment.
• Collaborate with cross-functional teams to integrate specialized AI models into enterprise-level applications.
• Monitor and refine production models to ensure accuracy, stability, and efficiency at scale.

Skills

PyTorch

Python

Distributed training

GPU optimization

Mixed-precision training

Model training pipelines

English

Job description

BairesDev is seeking a Deep Learning Engineer to design and implement advanced neural network architectures, bridging research and production-grade software. You will optimize models for performance and scalability in a fully remote setting.

The role emphasizes PyTorch and Python, distributed training, GPU optimization, and end-to-end pipelines from data preprocessing to deployment, with a global, Top 1% talent culture and flexible hours.