ML Infrastructure Engineer

Awake Solutions; Mexico; On-site; MXN 23,000 - 37,000; Full time

Benefits offered by this job

Competitive salary

Equity

GPU credits

Research budget

Conference support

Home office stipend

Job summary

Awake Solutions is seeking an ML Infrastructure Engineer to design and operate scalable infrastructure for training and serving large ML workloads with a focus on cost-efficiency, reliability and reproducibility.

You will architect and maintain GPU/TPU clusters, implement storage and feature stores, and automate capacity planning and scheduling for training workloads. Collaboration on security and multi-tenancy will be essential to support research infra.

Qualifications

• 4+ years in infra engineering with experience in cloud GPU/accelerator environments.
• Experience with cluster orchestration, provisioning and performance tuning.
• Familiarity with storage systems, feature stores and large-data workflows.
• Strong scripting and automation skills (Python, Bash, Terraform).

Responsibilities

• Architect and maintain scalable GPU/TPU clusters and provisioning workflows.
• Implement data storage, versioning and feature store infrastructure.
• Automate capacity planning, cost controls and job scheduling for training workloads.
• Collaborate on security, multi-tenancy and access patterns for research infra.

Skills

Python

Bash

Terraform

GPU/TPU infrastructure

Cluster orchestration

Tools

Kubernetes

Job description

We are looking for a

ML Infrastructure Engineer

Design and operate scalable infrastructure for training and serving large ML workloads, focusing on cost-efficiency, reliability and reproducibility.

Tasks

• Architect and maintain scalable GPU/TPU clusters and provisioning workflows.
• Implement data storage, versioning and feature store infrastructure.
• Automate capacity planning, cost controls and job scheduling for training workloads.
• Collaborate on security, multi-tenancy and access patterns for research infra.

Requirements

• 4+ years in infra engineering with experience in cloud GPU/accelerator environments.
• Experience with cluster orchestration, provisioning and performance tuning.
• Familiarity with storage systems, feature stores and large-data workflows.
• Strong scripting and automation skills (Python, Bash, Terraform).

Benefits

• Competitive salary + equity
• GPU/TPU credits & dedicated research budget
• Conference & training support
• Home office & equipment stipend

Job details

Job type: Full-time

Location: Hybrid - In-house (Primary) / Remote

Salary: ₹130k - ₹210k INR (depending on experience)