Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.
We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.
In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.
You will be:- owning the machine learning platform infrastructure as part of the Data Infrastructure team, which operates the company-wide GCP data and ML platform,
- owning Vertex AI, Kubeflow Pipelines, and GKE-based training and serving infrastructure, keeping it reliable, secure, and cost-efficient,
- building templates, CI/CD, and self-service workflows that enable data scientists to ship models without filing tickets,
- managing the model lifecycle, including model registry, versioning, deployment, rollback, and monitoring for drift and serving health,
- supporting feature and training data flows across BigQuery and Airflow, in collaboration with data platform engineers,
- managing infrastructure through GitOps with Config Sync, applying least-privilege access for PII and policy-tagged data,
- managing GPU and compute usage, quotas, and per-team spend visibility,
- taking end-to-end ownership of the platform that vertical teams use to build, train, and serve their models.
- 5+ years in MLOps, ML platform or platform engineering, including at least 2 years owning production ML infrastructure end to end,
- hands-on production experience with GCP, specifically Vertex AI, GKE and BigQuery,
- strong Kubernetes expertise, including running and debugging clusters independently,
- pipeline orchestration with Kubeflow Pipelines or Vertex AI Pipelines, plus Airflow,
- GitOps for infrastructure (Config Sync or similar) and CI/CD for model deployment,
- production-grade Python skills, including testing and packaging,
- a platform mindset: experience building documented, self-service tooling for other teams, with SLOs,
- ability to work independently as the single owner of a company-wide platform.
Work from the European Union region and a work permit are required.
- streaming features or online inference using Dataflow/Flink and Kafka,
- feature stores such as Vertex AI Feature Store or Feast, and model monitoring tooling,
- LLM serving and evaluation on Vertex AI or similar platforms,
- GPU scheduling and cost optimisation on GKE,
- Data governance experience (DataHub, policy tags) and privacy regulations such as GDPR or DPDP,
- experience with high-scale consumer products.
CV review – HR call – Interview – Client Interview – Decision
Skills Required
- 5+ years of experience in MLOps, ML platform, or platform engineering
- At least 2 years owning production ML infrastructure end to end
- Production experience with GCP, specifically Vertex AI, GKE, and BigQuery
- Strong Kubernetes expertise, including independently running and debugging clusters
- Experience with Kubeflow Pipelines or Vertex AI Pipelines and Airflow
- Experience with GitOps infrastructure management, including Config Sync or similar tools
- Experience with CI/CD for model deployment
- Production-grade Python skills, including testing and packaging
- Experience building documented, self-service tooling for other teams with SLOs
- Ability to work independently as the single owner of a company-wide platform
- Work from the European Union region
- Valid work permit
- Experience with streaming features or online inference using Dataflow, Flink, or Kafka
- Experience with feature stores such as Vertex AI Feature Store or Feast
- Experience with model monitoring tooling
- Experience with LLM serving and evaluation on Vertex AI or similar platforms
- Experience with GPU scheduling and cost optimization on GKE
- Data governance experience with DataHub or policy tags
- Knowledge of privacy regulations such as GDPR or DPDP
- Experience with high-scale consumer products
Xebia Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Xebia and has not been reviewed or approved by Xebia.
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Healthcare Strength — U.S. offerings include health, dental, and vision insurance alongside an Employee Assistance Program, strengthening total compensation where available.
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Leave & Time Off Breadth — Vacation/PTO and paid holidays, with mentions of parental leave in certain regions, broaden time-off options and support work-life balance.
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Retirement Support — A U.S. 401(k) plan with matching is noted, enhancing long-term financial benefits as part of total rewards.
Xebia Insights
What We Do
We are a pioneering IT consultancy company, following 1 mission, 4 values, and 4 business principles. WHO WE ARE With over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Founded in 2001, Xebia was the first Dutch organization to embrace the Agile way of working, with gurus like Jeff Sutherland. Since then, we have grown from a Java company into a full-service digital consulting company with 4500+ professionals working on a worldwide ambition. We are organized in complementary chapters – teams with a tremendous amount of knowledge and experience within a particular field, such as Agile, DevOps, Data and AI, Cloud, Software Technology, Low Code, and Microsoft. We help the world’s top 250 companies and category leaders overcome digital challenges, embrace innovation, adopt new technology, and implement new business models. In addition to high-quality consulting, we also provide offshoring and nearshoring services. WHAT WE DO ★ Digital Strategy ★ DevOps and SRE ★ Agile ★ Data and AI ★ Cloud ★ Microsoft Solutions ★ Software Technology ★ Security ★ Low Code ★ Xebia Academy HOW WE ARE ORGANIZED Xebia has launched specific labels, like GoDataDriven, Binx, Xpirit, Qxperts, Stackstate, Instruqt, Xccelerated, and Xebia Academy Complementing our organic growth, other specialized companies join our successful journey and also operate within the Xebia network under their own brand name, like Appcino, coMakeIt, g-company, Oblivion, PGS Software, and SwissQ. Together we are Xebia. With 17 offices in Atlanta, San Francisco, UK, Vietnam, Canada, Amsterdam, and Hilversum (the Netherlands), Belgium, Germany, Gurgaon, Jaipur, Hyderabad, Pune, Bangalore, Poland, Melbourne, Mexico, and Dubai. ✉️ [email protected]
