Xebia
IT Consultancy • Continuous Delivery • Offshore Services • Deployment Automation • Digital Transformation
Machine Learning Engineer
December 12
Xebia
IT Consultancy • Continuous Delivery • Offshore Services • Deployment Automation • Digital Transformation
Description
• working with data scientists and analysts to create and deploy new models and ML systems • implement end-to-end solutions across the full breadth of ML model development lifecycle • working hand in hand with the scientists from the point of data exploration for model development to the point of building features, ML pipelines and deploying them in production • working on batch and real time models, and operational support • establishing scalable, efficient, automated processes for data analyses, model development, validation and implementation • writing efficient and scalable software to ship products in an iterative, continual-release environment • writing optimized data pipelines to support machine learning models • contributing to and promoting good software engineering practices across the team and build cloud native software for ML pipelines • contributing to and re-using community best practice
Requirements
• ability to start immediately • openness to work daily between till 18-19.00 pm CET • university or advanced degree in engineering, computer science, mathematics, or a related field • 3+ years' experience developing and deploying machine learning systems into production • experience working with big data tools: Spark, Hadoop, Kafka, etc. • experience with at least one cloud provider solution (AWS, GCP, Azure) and understanding of serverless code development ( GCP experience preferred ) • efficiency with object-oriented/object function scripting languages ( Python required ) • efficiency with Python data-handling libraries like Pandas or Pyspark • efficiency in SQL for data consumption and transformation • expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, continuous deployment, code reviews, design documentation • working experience with native ML orchestration systems such as Kubeflow, Vertex AI Pipelines, Airflow, TFX • good verbal and written communication skills in English • Work from the European Union region and a work permit are required • Nice to have: • experience in working with SparkSQL, BigQuery SQL dialects • relevant working experience with Docker and Kubernetes • knowledge of data pipeline and workflow management tools • expertise in data engineering, analysis and processing (e.g. designing and maintaining ETLs, validating data and detecting quality issues) • knowledge in statistics and machine learning • previous experience developing predictive models in a production environment • MLOps and model integration into larger scale applications
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