Machine Learning Engineer, Recommendations

Role Overview

• Own the production recommendation infrastructure: maintain and improve the systems that serve personalized content to millions of users, ensuring reliability, low latency, and scalability as the catalog and user base grow.
• Research and prototype advanced recommendation algorithms: explore newer approaches
• deep learning-based models, contextual bandits, session-based recommendations, graph-based methods
• evaluate their potential, and run controlled experiments to validate uplift before production.
• Produce ML models and pipelines: take prototypes (from yourself or from the team's Data Scientist) and turn them into production-grade, monitored, maintainable features integrated into the live recommendation engine.
• Design scalable infrastructure: anticipate bottlenecks and design systems that can handle larger catalogs, more complex segmentations, and higher traffic
• including serving layer optimization, caching strategies, and pipeline orchestration.
• Build and maintain data pipelines in DBT and Databricks, ensuring clean transformations, data quality, and robust experimentation frameworks that the team can rely on.
• Monitor model health in production: define retraining strategies, detect drift, and ensure recommendation quality is measured and maintained over time.
• Collaborate closely with the Data Scientist and Senior Analyst to translate statistical insights and business requirements into engineering decisions.

Requirements

• Python for ML and infrastructure: strong Python skills applied to model training, evaluation, deployment, and pipeline scripting. Writes production-quality, testable, version-controlled code
• not just notebooks.
• SQL and DBT: solid SQL and hands-on DBT experience to build and maintain reliable transformation pipelines with clear data lineage and quality controls.
• ML production on AWS: hands-on experience deploying and monitoring ML models using AWS services (SageMaker, Lambda, ECS, Step Functions). Understands model drift, monitoring strategies, and retraining triggers.
• Batch ML model training and evaluation pipelines: design, build, and maintain scalable machine learning training and evaluation pipelines that support recommendation systems and related personalization use cases.
• Advanced ML algorithms: familiarity with recommendation techniques beyond collaborative filtering
• e.g. neural approaches (two-tower models, transformers for sequences), contextual bandits, learning-to-rank. Knows how to evaluate and compare them rigorously.
• Orchestration and CI/CD: experience with orchestration tools (Airflow, Prefect, or Dagster) for reliable, observable pipelines, and comfort with Git and CI/CD workflows for ML systems.
• Scalability and system design mindset: can anticipate infrastructure bottlenecks, reason through architecture trade-offs (batch vs. streaming, horizontal vs. vertical scaling), and connect engineering decisions to business outcomes.
• Nice to have: Experience with real-time or low-latency serving layers (Redis, DynamoDB or equivalent)
• the system is currently batch, but session-level adaptation is a future direction.
• Experience with experimentation frameworks for ML systems, including online evaluation of recommendation algorithms (A/B tests, interleaving, counterfactual evaluation).

Tech Stack

• Airflow
• AWS
• DynamoDB
• Python
• Redis
• SQL

Benefits

• Career Growth: Your growth drives our success! We invest in your development up to €2,000 per year for books and training; so you can keep learning and growing with us.
• Remote-Friendly: Work from where you’re most productive, home or our offices in Madrid, anywhere within a 2-hour difference from Spain (GMT+1).
• Stock Options: Your contribution matters! You'll receive stock options, giving you the opportunity to own part of the company and share in its success.
• Home Office Setup: Create your ideal workspace with a €400 allowance for setup and €35/month for remote work expenses, because comfort fuels creativity!
• Meal Allowances: Get €60/month on your Cobee card to enjoy meals at restaurants or food delivery, good food makes everything better!
• Flexible Compensation: Manage your meal, transport and childcare expenses easily with Cobee, integrating them directly into your payroll.
• Health Insurance: Access private health coverage at exclusive rates through Adeslas, seamlessly deducted from your payroll, quality care made simple.
• Language Lessons: Learning never stops! Enjoy free language classes in Spanish and English, to sharpen your skills and stay connected in a global team.
• Visa Sponsorship: If you need a visa to work in the EU, we’ll handle the process and cover the costs to make your transition seamless.
• Company events: Yes! We’re a fully remote team spread across different countries, but we love getting together from time to time in different corners of Spain, for team gatherings and recharging at our amazing off-sites!