Senior Remote ML Infrastructure Engineer

BairesDev; Peru (IL); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Remote work

Payment in USD

Home setup provided

Flexible hours

Parental leave & holidays

Mentorship & growth

Job summary

BairesDev is seeking an ML Infrastructure Engineer to design and manage robust GPU clusters and scalable training frameworks. You will empower ML teams by building enterprise-scale infrastructure for training and inference, with a focus on reliability, performance, and scalability.

You will collaborate with data science and engineering teams, leveraging container orchestration and high-performance networking to enable efficient ML workflows in a 100% remote setting.

Qualifications

• 8+ years of experience in Infrastructure Engineering, DevOps, or ML Infrastructure.
• Proven expertise designing and managing large-scale GPU clusters for AI workloads.
• Hands-on experience with distributed training frameworks and model serving at scale.
• Strong background building and automating ML pipelines infrastructure.

Responsibilities

• Design and architect enterprise-scale GPU clusters to support AI workloads.
• Implement and optimize distributed training frameworks to reduce development cycles.
• Build and maintain high-performance model serving infrastructure for low-latency production inference.
• Manage large-scale orchestration of ML workloads to maximize hardware utilization.
• Collaborate with data science teams to define infrastructure standards and resource needs.

Skills

GPU clusters

Distributed training

Model serving at scale

Container orchestration

High-performance networking

English proficiency

Job description

BairesDev is seeking an ML Infrastructure Engineer to design and manage robust GPU clusters and scalable training frameworks. You will empower ML teams by building enterprise-scale infrastructure for training and inference, with a focus on reliability, performance, and scalability.

You will collaborate with data science and engineering teams, leveraging container orchestration and high-performance networking to enable efficient ML workflows in a 100% remote setting.