MLOps Engineer (Enterprise AI Platform)

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stermedia.ai

Role overview

Summary

This role focuses on building and automating production-grade AI and Machine Learning solutions. You will work closely with Data Scientists, ML Engineers, and Cloud Engineers to ensure efficient deployment and maintenance of machine learning systems within the enterprise AI infrastructure.

Qualifications

Experience in MLOps or related field.
Knowledge of cloud-native technologies.
Familiarity with automation tools for ML workflows.
Experience in deploying and maintaining machine learning systems.
Preferred: Understanding of DevOps practices.

Responsibilities

Build production-grade AI and Machine Learning solutions.
Automate ML workflows and improve model deployment processes.
Collaborate with Data Scientists, ML Engineers, and Cloud Engineers.
Transform ML models into reliable, scalable, and production-ready services.

Key facts

Remote from: Poland, Europe, European Union, EMEA
Full time
MLOps Engineer
English

Hard skills

Other skills

Collaboration

About the company

stermedia.ai

IT Services & Consulting
TPE
11–50

🧠Since 2009 we have been helping companies and startups to engineer powerful web and mobile applications based on AI, with user-friendly UX and UI. 🗣86% of our clients chose Stermedia based on recommendations. We are part of Euvic Group. 🎯6 years in the artificial intelligence business 🎓Dedicated team of data scientists (Masters and PhDs in mathematics, statistics) and Senior Python Developers 🎖Polish data scientists are the 10th best in the world according to Coursera Global Skills Index 📘Artificial intelligence (machine learning/ deep learning) - NLP (Natural Language Processing), deep data analysis, image, video & voice processing and more 📙Software Development - web and mobile development 📗Product Design - UX/ UI

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Job description

We are looking for an MLOps Engineer to help build, automate, and scale production-grade AI and Machine Learning solutions.

You will work at the intersection of Machine Learning, Cloud Engineering, and DevOps, helping transform ML models into reliable, scalable, and production-ready services.

This role offers the opportunity to work with modern cloud-native technologies, automate ML workflows, improve model deployment processes, and contribute to the development of enterprise AI infrastructure. You will collaborate with Data Scientists, ML Engineers, and Cloud Engineers to ensure that machine learning systems are efficiently deployed, monitored, and maintained.