Remote Deep Learning ML Engineer - PyTorch & Distributed

BairesDev; Peru (IL); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote work

USD compensation

Home office setup

Flexible hours

Paid parental leave

Vacations and holidays

Global Top 1% talent

Mentorship and growth

Job summary

BairesDev, a leader in technology projects for 15+ years, offers a 100% remote ML Engineer role focused on Deep Learning. You will design and optimize neural networks at scale, collaborating with teams across distributed systems to deliver impact for global clients.

The role emphasizes Python and PyTorch with custom architectures and advanced training techniques to boost performance in production environments. Strong English communication is required.

Qualifications

• 4+ years of software engineering experience with a focus on Deep Learning.
• Proven PyTorch expertise and designing custom model architectures.
• Hands-on experience with distributed training and GPU optimization.
• Proficiency in Python programming and training optimization.

Responsibilities

• Design, build, and train large-scale deep learning models using PyTorch.
• Develop custom model architectures tailored to data types and requirements.
• Implement distributed training strategies to reduce training time.
• Optimize GPU utilization and model performance with mixed-precision training.
• Collaborate with engineering teams to integrate models into production systems.
• Monitor and refine model performance for real-world scalability.

Skills

Deep Learning

PyTorch

Distributed Training

GPU Optimization

Python

English

Tools

CUDA

Job description

BairesDev, a leader in technology projects for 15+ years, offers a 100% remote ML Engineer role focused on Deep Learning. You will design and optimize neural networks at scale, collaborating with teams across distributed systems to deliver impact for global clients.

The role emphasizes Python and PyTorch with custom architectures and advanced training techniques to boost performance in production environments. Strong English communication is required.