15 days ago
Rome, ItalySenior
Responsibilities
- Design, build, deploy, and monitor production machine learning models and pipelines.
- Build and maintain high-volume feature engineering and data pipelines using Spark, Databricks, Python, and SQL.
- Implement MLOps practices including model registries, experiment tracking, offline and online evaluation, and data/model drift and quality monitoring.
- Integrate audience models with the Audience API, User Profile API, Kafka Topics, and activation integrations including DV360, Braze, and TTD.
- Design offline evaluations and A/B tests, tune models and hyperparameters, and identify new data signals.
- Plan and execute modeling and data-pipeline initiatives in accordance with GDPR, CCPA, and consent-management requirements.
- Collaborate with Product Analytics, Marketing Science, Data Engineers, and Software Engineers to support revenue objectives.
- Participate in the team's on-call rotation and use AI-assisted development tools to improve engineering throughput.
Requirements
- Proven experience across the full production ML lifecycle, including feature engineering, model training, evaluation, deployment, and monitoring.
- Strong proficiency in Python, Spark, SQL, and Databricks, with experience operating distributed data pipelines at scale.
- Strong software engineering fundamentals and experience owning production backend and data systems end to end.
- Solid grounding in statistics, model selection, hyperparameter tuning, and experiment design including A/B testing.
- Experience with ML lifecycle tools such as MLflow or equivalent, model registries, and production monitoring for drift and quality.
- Hands-on experience using AI development tools such as Cursor or Claude Code.
- Bachelor's degree in Computer Science, Mathematics, Physics, Engineering, or a related quantitative field.
- Fluent written and spoken English with availability overlapping North American hours from 9 a.m. to 12 p.m. EST.
- Ad-tech or programmatic advertising experience is preferred.
- Privacy engineering experience, deep Databricks platform administration knowledge, and familiarity with LLM platforms and embedding research are preferred.
Benefits
- Flexible hybrid work model with full remote availability from Europe and offices in Milan, Barcelona, and Sofia.
- Learning opportunities and regular feedback sessions.
- Central modern offices with fresh snacks, coffee including vegan options, and ergonomic setups.
- Team events including offsites, happy hours, company parties, and celebrations.
- Necessary equipment is provided for home or office workspaces.
- Additional country-specific benefits may apply based on local contracts and practices.
Tech Stack
Categories
Data EngineeringML Engineering
About ShopFully
ShopFully builds a “drive-to-store” digital advertising platform that connects online shoppers with local retailers’ offers through its apps, websites, and a large publisher network. Retailers and brands use its AI-based targeting and ad products to promote weekly deals and measure in-store impact, paying for media and campaign services. Founded in 2012 and headquartered in Milan, it operates across 25 countries and reports connecting around 200 million shoppers for hundreds of retail clients.