DevOps Engineer

Enfint; Lisboa; Presencial; EUR 65 000 - 90 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Flexible schedule

Medical insurance

Sports benefits

Corporate events

Professional development

Well-equipped office

Resumo da oferta

Enfint seeks a senior infrastructure/ML Ops engineer to lead the design, evolution, and long-term technical direction of scalable, multi-GPU infrastructure and model training platforms across cloud environments.

You will drive reliability, performance, and cost-efficiency at scale, build automation, and mentor engineers while advancing CI/CD, monitoring, and on-call support across Linux-based, GPU-heavy systems.

Qualificações

• Production-grade, hands-on experience with Kubernetes and cloud environments.
• Experience building and operating CI/CD pipelines, including self-hosted build runners (GitHub Actions).
• Deep hands-on experience with monitoring and alerting stacks (Prometheus and Grafana).
• Strong foundational knowledge in Linux administration, containerization, and container orchestration.
• Solid automation and scripting skills utilizing Python and Bash.
• Flexibility to participate in an on-call rota for urgent issues outside of regular business hours.
• Nice to have: CKA certification and GPU-accelerated Kubernetes clusters experience.

Responsabilidades

• Lead the design, evolution, and long-term technical direction of scalable, multi-GPU infrastructure and model training platforms.
• Drive reliability, performance, and cost-efficiency at scale across cloud environments.
• Build and evolve infrastructure-as-code and automation for provisioning, orchestration, and lifecycle management.
• Architect and improve CI/CD systems for infrastructure and ML training workflows.
• Partner with ML engineers and researchers to enable efficient experimentation and productionization.
• Lead troubleshooting of complex system issues in distributed, GPU-heavy environments.
• Define and implement best practices for infra, DevOps, and MLOps across the organization.
• Document architecture, systems, and key technical decisions.

Conhecimentos

Linux administration

Containerization

Automation scripting

CI/CD operations

Ferramentas

Kubernetes

Terraform

Helm

AWS

GitHub Actions

Prometheus

Grafana

Python

Bash

Karpenter

FSx for Lustre

EFS

Descrição da oferta de emprego

The company creates advanced, reliable, and commercially scalable humanoid robots, focusing on next-gen labor automation units designed to integrate into daily life and amplify human capacity through high-efficiency industrial applications.

Задачи

• Lead the design, evolution, and long-term technical direction of scalable, multi-GPU infrastructure and model training platforms across cloud environments;
• Drive reliability, performance, and cost-efficiency at scale, including optimization of distributed training workloads;
• Build and evolve infrastructure-as-code and automation for provisioning, orchestration, and lifecycle management;
• Architect and improve CI/CD systems for both infrastructure and ML training workflows;
• Partner with ML engineers and researchers to enable efficient experimentation and productionization;
• Lead the troubleshooting and resolution of complex system issues across distributed, GPU-heavy environments;
• Define and implement best practices for infrastructure, DevOps, and MLOps across the organization;
• Mentor engineers and raise the bar for engineering quality and operational excellence;
• Document architecture, systems, and key technical decisions.

Требования

• Production-grade, hands-on experience with Kubernetes;
• Production-grade, hands-on experience using Terraform;
• Experience with Kubernetes application packaging and release management using Helm;
• Hands-on experience operating heavy workloads on AWS;
• Experience building and operating CI/CD pipelines, including self-hosted build runners (GitHub Actions);
• Deep hands-on experience with monitoring and alerting stacks (Prometheus and Grafana);
• Strong foundational knowledge in Linux administration, containerization, and container orchestration;
• Solid automation and scripting skills utilizing Python and Bash;
• Flexibility to participate in an on-call rota for urgent issues outside of regular business hours;
• Nice to have: CKA certification, hands-on experience operating GPU-accelerated Kubernetes clusters (NVIDIA), experience with gang scheduling, resource allocation, and fair-sharing for large-scale ML training, experience with cluster autoscaling/dynamic node provisioning (Karpenter) and high-performance shared storage systems (FSx for Lustre, EFS).

Условия

• Competitive salary;
• Flexible schedule;
• Medical insurance;
• Sports benefits;
• Corporate social events;
• Professional development opportunities;
• Well-equipped office.