Xebia
Xebia is a pioneering Software Engineering and IT consultancy company that specializes in digital transformation, agile transformation, cloud computing, data and AI, DevOps, and intelligent automation. The company focuses on creating digital leaders by leveraging advanced technology and providing strategic solutions to diverse industries, including Banking, Healthcare, Retail, and more. With a global presence and a strong partnership with GitHub and Google Cloud, Xebia provides end-to-end services that empower organizations to maximize their technology potential and drive innovation.
IT Consultancy • Continuous Delivery • Offshore Services • Deployment Automation • Digital Transformation
Senior MLOps Engineer
February 11
Airflow
AWS
Azure
BigQuery
Cloud
Docker
Google Cloud Platform
Kubernetes
Python
PyTorch
Scikit-Learn
Tensorflow
Xebia
Xebia is a pioneering Software Engineering and IT consultancy company that specializes in digital transformation, agile transformation, cloud computing, data and AI, DevOps, and intelligent automation. The company focuses on creating digital leaders by leveraging advanced technology and providing strategic solutions to diverse industries, including Banking, Healthcare, Retail, and more. With a global presence and a strong partnership with GitHub and Google Cloud, Xebia provides end-to-end services that empower organizations to maximize their technology potential and drive innovation.
IT Consultancy • Continuous Delivery • Offshore Services • Deployment Automation • Digital Transformation
📋 Description
• working with data scientists and analysts to create and deploy new product features on the e-commerce website, in-store portals, and clients’ mobile apps • establishing scalable, efficient, automated processes for data analysis, model development, validation, and implementation • writing efficient and scalable software to ship products in an iterative, continual-release environment • contributing to and promoting good software engineering practices across the team and building cloud-native software for ML pipelines • contributing to and reusing community best practices.
🎯 Requirements
• willingness to work daily 9AM - 5PM CET, once in a while until 6-7PM • university degree or advanced degree in engineering, computer science, mathematics, or a related field • 10+ years of experience as a data engineer or software developer • 3+ years of experience developing and deploying machine learning systems into production • proficiency in Python • experience with at least one Cloud provider (AWS, GCP, Azure) and understanding of serverless code development • working experience with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, TFX • relevant working experience with Docker, Kubernetes and GitHub Actions • knowledge of data pipeline and workflow management tools • expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation • experience with Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow or PyTorch • exposure to GenAI and solid understanding of multimodal AI via HuggingFace, Llama, VertexAI, AWS Bedrock or GPT • very good verbal and written communication skills in English • Work from European Union region and a work permit are required
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