MLOps Engineer

Summary

Join Xebia, a global leader in digital solutions, and contribute to the development and deployment of machine learning systems for e-commerce and other platforms. As a Data Engineer, you will collaborate with data scientists and analysts, build scalable data pipelines, and implement efficient software solutions. This role requires a strong background in software engineering, machine learning, and cloud technologies. You will work with cutting-edge tools and technologies, contributing to a team focused on innovation and excellence. The position is based in Moldova and requires immediate availability. Apply now to begin your journey with Xebia.

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
• 2+ years of experience developing and deploying machine learning systems into production
• 3+ 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