Senior Machine Learning Engineer

December 12, 2024

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Xebia

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Xebia is a leading Software Engineering and IT consultancy company that specializes in digital transformation, agile transformation, cloud solutions, data and AI, DevOps, SRE, and other IT services. It helps businesses across various industries to harness new technologies for sustainable growth and improved efficiency. With a global presence, Xebia partners with companies to provide high-quality consulting, training, and managed services. Known for being at the forefront of technological innovation, Xebia is recognized for its deep collaboration with platforms like GitHub and is committed to making AI integration in software development easier and more accessible. The company serves a wide range of sectors including finance, technology, healthcare, and manufacturing, aiming to create digital leaders and empower organizations to achieve their strategic goals through cutting-edge technology and people-centric approaches.

IT Consultancy • Continuous Delivery • Offshore Services • Deployment Automation • Digital Transformation

5001 - 10000 employees

🏢 Enterprise

🤖 Artificial Intelligence

☁️ SaaS

📋 Description

• implementing end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, model retraining, model deployment and metadata tracking • identifying new opportunities to improve business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset • working with data scientists and analysts to create and deploy new product features on the ecommerce website, in-store portals and client’s mobile app • 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 • contributing to and promoting good software engineering practices across the team and build cloud native software for ML pipelines • contributing to and re-use community best practices.

🎯 Requirements

• ability to start immediately • openness to work daily between till 19.00 pm CET • university or advanced degree in engineering, computer science, mathematics, or a related field • 7+ years experience developing and deploying machine learning systems into production • experience working with a variety of relational SQL and NoSQL databases • experience working with big data tools: Hadoop, Spark, Kafka, etc. • experience with at least one cloud provider solution (AWS, GCP, Azure) and understanding of severless code development • experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. • previous experience developing predictive models in a production environment • MLOps and model integration into larger scale applications • experience with Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow or PyTorch • exposition to GenAI and solid understanding of multimodal AI via HuggingFace, Llama, VertexAI, AWS Bedrock or GPT • 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 • working experience with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, TFX • very good verbal and written communication skills in English • good verbal and written communication skills in English. • Work from European Union region and work permit are required. • Nice to have: relevant working experience with Docker and Kubernetes.