Job description
Description
Who We Are
While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started.
What We Do
We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data-driven solutions, and next-gen apps using ML, LLMs, and Generative AI. Our clients include Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, and Allegro or InPost.
We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland!
Beyond Projects
What makes Xebia special? Our community. We run events like the Data&AI Warsaw Summit, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow.
What sets us apart?
Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself.
You will be:
collaborating with Platform Engineers to set the infrastructure required to run MLOps processes efficiently,
implementing ML workflows / automating CI/CD pipelines,
automating model deployment and implementing model monitoring,
collaborating with Platform Engineers to implement backup and disaster recovery processes for ML workflows, especially models and experiments,
collaborating with stakeholders to understand the key challenges and inefficiencies of Machine Learning project lifecycles within the company,
keeping on top of the latest trends and advancements in data engineering and machine learning.
Requirements
Your profile:
2+ years of experience developing and deploying machine learning systems into production,
5+ years of experience as a MLOps engineer or data engineer or software developer
hands-on experience with cloud environments (AWS / Azure / GCP),
experience with tools such as Spark, PyTorch, TensorFlow and MLFlow,
knowledge of DevOps practices and tools, including Terraform,
experience with Docker and Kubernetes,
understanding of continuous integration and continuous deployment (CI/CD) practices, as well as experience with related tools like GitHub Actions or GitLab CI,
excellent verbal and written communication skills in English.
Nice to have:
Cloud (Azure, AWS, GCP) certification is a big plus,
familiarity with Amazon SageMaker / Azure Machine Learning/ Azure Machine Learning / VertexAI is nice to have.
Work from the European Union region and a work permit are required.
Candidates must have an active VAT status in the EU VIES registry: https://ec.europa.eu/taxation_customs/vies/
Recruitment Process:
CV review – HR call – Interview (with Live-coding) – Client Interview (with Live-coding) – Hiring Manager Interview - Decision
