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 ML Engineer
April 6
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
• ML Engineers share fundamental responsibilities in streamlining machine learning project lifecycles. • They are dedicated to designing and automating workflows, implementing CI/CD pipelines, ensuring reproducibility, and providing reliable experiment tracking. • Responsibilities include collaborating with stakeholders and platform engineers, leveraging expertise in infrastructure setup, model deployment, monitoring, and proficiency with cloud platforms and data processing. • Role involves developing new algorithms and optimizing existing ones, adding significant functionality based on user feedback, optimizing ML pipelines, taking initiative and proposing new approaches, designing and architecting machine learning workflows, implementing ML workflows, and collaborating with Platform Engineers to set the infrastructure for MLOps processes efficiently.
🎯 Requirements
• 5+ years of experience in Python • proficiency in the NumPy, Pandas, and SciPy stack • strong SQL skills • understanding of fundamental statistical concepts (e.g., Bayes’ rule, linear regression, maximum likelihood estimation) • experience with containerization technologies like Docker • familiarity with AWS, Azure or GCP • comfortable using Git • knowledge of Docker, and Kubernetes • Cloud (Azure, AWS, GCP) certification is a big plus • excellent verbal and written communication skills in English • knowledge of Airflow or, Kedro is a big plus
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