Data Engineer - ML & GenAI Platform

Wix makes it possible for anyone to succeed online. Since 2006, we’ve grown to around 5,500 employees in 22 countries, launched over 40 products, and serve over 243 million users and their visitors worldwide. Today, AI and data are at the core of how we build: from intelligent website creation and personalization to GenAI tools that help our users run and grow their businesses.

We’re continuously evolving Wix into an AI‑powered platform for web creation and business management. Our goal is to become the main engine of the Internet, combining powerful infrastructure, advanced ML and GenAI capabilities, and an open ecosystem so we can create a smarter, more accessible web for all.

Job Description

As a data engineer in Wix’s data science group, you’ll build, use, and enhance our ML and GenAI platforms, powering data products and LLM-based services across Wix. You’ll design and operate data and MLOps infrastructure for batch inference, knowledge-base workflows, evaluation metrics, and fine-tuning pipelines. Collaborating with data scientists, product managers, and engineers, you’ll bring AI features into production at scale.

• Extend and implement new capabilities in ML and GenAI platforms
• Design and maintain scalable, reliable data architectures and pipelines for model training, LLM fine-tuning, inference, and evaluation
• Develop and maintain Airflow DAGs for metrics calculation, batch inference, KB workflows, and other data science projects
• Collaborate with data scientists and engineers to integrate models and GenAI features into production systems
• Ensure high-quality code through best practices in testing, code reviews, documentation, and CI/CD for data and ML workloads
• Work with tools and platforms like Airflow, Spark, Docker, Python Serverless, Kafka, and multiple cloud environments to deliver scalable, cost-effective GenAI solutions
  
  

• 3+ years of experience in data engineering or building data-intensive systems
• Proficient in Python and SQL with hands-on experience building data pipelines and production-grade services
• Practical experience with Airflow, Spark, and Docker
• Knowledge of or strong interest in data science and machine learning
• Experience or strong interest in GenAI platforms and LLM-based services
• Excellent communication and collaboration skills to work with cross-team stakeholders
• Experience in cloud environments like AWS and/or GCP – an advantage