Senior MLOps

Summary

Join Xebia, a global leader in digital solutions, and contribute to the development and deployment of new product features for e-commerce websites, in-store portals, and mobile apps. As a Data Engineer, you will collaborate with data scientists and analysts, establishing efficient automated processes for data analysis and model implementation. You will write scalable software, contribute to best practices, and build cloud-native software for ML pipelines. This role requires 3+ years of experience in deploying machine learning systems and 5+ years as a data engineer or software developer. The position is based in Moldova and requires proficiency in Python and experience with specific technologies. Xebia offers a dynamic work environment and opportunities for professional growth.

Requirements

• Ability to start immediately
• Willingness to work daily until 18-19:00 CET
• University degree or advanced degree in engineering, computer science, mathematics, or a related field
• 3+ years of experience developing and deploying machine learning systems into production
• 5+ years of experience as a data engineer or software developer
• Experience working with VertexAI, BigQuery and Dataproc
• Proficiency in Python
• 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
• This position is open only to candidates currently residing in Moldova and holding the legal right to work in Moldova

Responsibilities

• Work with data scientists and analysts to create and deploy new product features on the e-commerce website, in-store portals, and clients’ mobile apps
• Establish scalable, efficient, automated processes for data analysis, model development, validation, and implementation
• Write efficient and scalable software to ship products in an iterative, continual-release environment
• Contribute to and promote good software engineering practices across the team and building cloud-native software for ML pipelines
• Contribute to and reuse community best practices

Preferred Qualifications

• Relevant working experience with Docker and Kubernetes
• 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