Principal ML Ops Engineer (EMEA Remote)

Remote in Portugal·Full-time·Added 5 days ago

Pragmatike

19 open roles

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Overview

Job details

Full-time hours
Per the ad.
Fully remote
Only from certain places, per the ad: “Fully remote (EMEA timezone)”

Requirements

Have 4+ years of experience
Mid-level role.

The role

Pragmatike is recruiting on behalf of a fast-scaling, well-funded distributed cloud infrastructure startup building next-generation AI-native cloud services. The company is redefining how compute is delivered by providing GPU-powered infrastructure for AI/ML workloads, secure storage, and high-speed data transfer through a decentralized architecture that significantly reduces environmental impact compared to traditional cloud providers.

We are seeking a ML Ops Engineer with strong experience in production-grade model serving and infrastructure for AI systems. This is a highly technical, hands-on role focused on building scalable, reliable, and efficient ML inference platforms powering real-time AI applications.

You will be responsible for designing and operating the core infrastructure that serves machine learning models at scale. You will work closely with infrastructure, platform, and applied AI teams to ensure high availability, low latency, and cost-efficient inference systems. Strong ownership, production mindset, and experience with distributed GPU systems are essential.

What you'll do

Build and operate production-grade model serving infrastructure using frameworks such as vLLM, TGI, Triton, or equivalent
Design and implement robust deployment pipelines with blue/green and canary rollout strategies for ML models
Develop and maintain auto-scaling systems, multi-model serving architectures, and intelligent request routing layers
Optimize GPU utilization, memory efficiency, network throughput, and model artifact storage performance
Design observability systems for tracking inference latency, throughput, GPU usage, cost metrics, and system health
Manage model registries and CI/CD pipelines enabling automated and reproducible model deployments
Own the full lifecycle of ML systems from development through production, including operational support and on-call responsibilities
Define engineering best practices and contribute to platform scalability in a fast-moving startup environment

How you'll work

Location: Fully remote (EMEA timezone)
Start date: ASAP
Languages: Fluent English required
Industry: Cloud Computing / AI / European Deep-Tech SaaS

Requirements

What we're looking for

4+ years of experience in ML Ops, Platform Engineering, SRE, or similar infrastructure roles focused on ML systems
Hands-on experience with model serving frameworks such as vLLM, TGI, Triton, or equivalent
Strong background in container orchestration and operating GPU-based workloads in production
Experience with MLOps tooling including model registries, experiment tracking, and automated deployment pipelines
Proficiency in Python and infrastructure-as-code tools (e.g., Terraform, Helm, or similar)
Strong understanding of distributed systems, performance tuning, and production reliability engineering
Ability to effectively use AI coding assistants to accelerate development and debugging workflows
Ownership mindset with the ability to operate independently in a remote-first environment

Nice to have

Experience with ML platforms such as Kubeflow, MLflow, or KubeAI
Knowledge of GPU scheduling, CUDA/ROCm optimization, or multi-tenant inference systems
Experience with cost optimization across different GPU types and inference workloads
Background in early-stage startups or greenfield infrastructure projects
Proven experience building production systems from scratch rather than maintaining legacy platforms

About Pragmatike

Pragmatike is an IT services and consulting company specializing in cloud computing, data engineering, and machine learning operations (MLOps). The company helps enterprises build and scale their data and AI infrastructure, with a strong focus on Kubernetes, cloud-native architectures, and GPU-based AI workloads. Pragmatike operates as a remote-first organization, serving clients primarily across the EMEA region.

Pragmatike has a significant presence in Spain, with its headquarters in Madrid and a team of engineers working remotely across the country. The company is highly relevant to international professionals given its fully remote hiring model, which allows engineers to work from anywhere in Spain or the broader EMEA region. Their open roles in Spain, such as Principal ML Ops Engineer and AI Infrastructure Engineer, are well-suited for international talent looking to join a fast-growing, specialized cloud and AI consultancy.

Industry: IT Services
Founded: 2021
Employees: 50–200
Headquarters: Madrid, Spain

In their own words

About the company & team

Take ownership of critical infrastructure powering a rapidly scaling AI-native cloud platform
Build foundational ML inference systems from the ground up in a high-growth, well-funded startup
Work at the intersection of distributed systems, GPU computing, and sustainable cloud architecture
Gain deep expertise in next-generation AI infrastructure and large-scale model serving systems
Influence core engineering decisions and define best practices that will scale with the company.

Additional information

Pragmatike is committed to a fair, transparent, and inclusive recruitment process. We do not discriminate based on age, disability, gender, gender identity or expression, marital or civil partner status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation.

In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely, and used solely for recruitment purposes, including sharing it with our client(s) for employment consideration.

All open roles at Pragmatike