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ML Ops Engineer - EMEA Remote

PragmatikeUkraine
Remote Full-time

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Experience Level

Experience

Qualifications

Strong experience in ML Ops and production-grade model serving. Proficiency with GPU systems and distributed computing frameworks. Expertise in developing deployment strategies and managing CI/CD pipelines. Excellent problem-solving skills with a focus on performance optimization. Ability to work collaboratively in a fast-paced, team-oriented environment.

About the job

Location: Remote within EMEA time zones (including Ukraine)
Start date: ASAP
Languages: Fluent English required
Industry: Cloud Computing, AI, European Deep-Tech SaaS

Role Overview

Pragmatike is hiring an ML Ops Engineer to help build the backbone of a distributed cloud infrastructure startup. This well-funded company focuses on AI-native cloud services, offering GPU-powered compute for machine learning workloads, secure storage, and high-speed data transfer. The platform relies on a decentralized architecture designed to reduce environmental impact compared to traditional cloud providers.

This position centers on designing and operating scalable ML inference platforms for real-time AI applications. The role involves close collaboration with infrastructure, platform, and applied AI teams to deliver high availability, low latency, and cost-efficient model serving. A production mindset and hands-on experience with distributed GPU systems are essential.

What You Will Do

  • Build and maintain production-ready model serving infrastructure using frameworks such as vLLM, TGI, Triton, or similar tools.
  • Design and implement deployment pipelines with blue/green and canary rollout strategies for machine learning models.
  • Develop and support auto-scaling systems, multi-model serving solutions, and smart request routing layers.
  • Optimize GPU utilization, memory usage, network throughput, and model artifact storage performance.
  • Set up observability systems to monitor inference latency, throughput, GPU consumption, cost, and system health.
  • Manage model registries and CI/CD pipelines to automate and standardize model deployments.
  • Oversee the full ML systems lifecycle, from development through production operations, including on-call support.
  • Shape engineering best practices and contribute to platform scalability as the company grows.

Requirements

  • Proven experience in ML Ops and production model serving.
  • Hands-on background with GPU systems and distributed computing frameworks.
  • Skilled in deployment strategies and CI/CD pipeline management.
  • Strong problem-solving abilities, especially in performance tuning and optimization.
  • Comfort working collaboratively in a team-oriented, fast-moving setting.

About Pragmatike

Pragmatike is a cutting-edge startup specializing in cloud computing solutions, focusing on AI-native cloud services. The company is committed to sustainability and innovation, providing GPU-powered infrastructure that significantly reduces environmental impact while enhancing efficiency for AI and machine learning workloads.

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