Machine Learning Engineer, Recommendations

This is a fully remote position, open to applicants in Spain.

📋 Description

• Take charge of the production recommendation infrastructure: oversee and enhance the systems that deliver personalized content to millions of users, ensuring reliability, low latency, and scalability as the catalog and user base expand.

• Investigate and prototype cutting-edge recommendation algorithms: explore innovative approaches such as deep learning-based models, contextual bandits, session-based recommendations, and graph-based methods; assess their potential and conduct controlled experiments to validate improvements prior to production deployment.

• Develop ML models and pipelines: transform prototypes (from yourself or the team's Data Scientist) into production-quality, monitored, and maintainable features that are integrated into the live recommendation engine.

• Design scalable infrastructure: foresee potential bottlenecks and create systems capable of managing larger catalogs, more intricate segmentations, and increased traffic, including serving layer optimization, caching strategies, and pipeline orchestration.

• Construct and maintain data pipelines using DBT and Databricks, ensuring clean transformations, data integrity, and robust experimentation frameworks that the team can depend on.

• Monitor model performance in production: establish retraining strategies, detect drift, and ensure that the quality of recommendations is consistently measured and upheld over time.

• Work closely with the Data Scientist and Senior Analyst to convert statistical insights and business requirements into engineering decisions.

⛳️ Requirements

• Proficient in Python for ML and infrastructure: strong Python skills applied to model training, evaluation, deployment, and pipeline scripting. Capable of writing production-quality, testable, version-controlled code - not just notebooks.

• SQL and DBT expertise: solid SQL skills and hands-on experience with DBT to construct and maintain reliable transformation pipelines with clear data lineage and quality controls.

• Experience with ML production on AWS: practical experience in deploying and monitoring ML models using AWS services (SageMaker, Lambda, ECS, Step Functions). Knowledgeable about model drift, monitoring strategies, and retraining triggers.

• Design and maintenance of batch ML model training and evaluation pipelines: create, build, and uphold scalable machine learning training and evaluation pipelines that support recommendation systems and related personalization use cases.

• Familiarity with advanced ML algorithms: understanding of recommendation techniques beyond collaborative filtering, including neural approaches (two-tower models, transformers for sequences), contextual bandits, and learning-to-rank. Capable of evaluating and rigorously comparing these methods.

• Orchestration and CI/CD experience: knowledgeable in using orchestration tools (Airflow, Prefect, or Dagster) for dependable and observable pipelines, and comfortable with Git and CI/CD workflows for ML systems.

• Scalability and system design mindset: ability to anticipate infrastructure bottlenecks, evaluate architectural trade-offs (batch vs. streaming, horizontal vs. vertical scaling), and connect engineering choices to business outcomes.

• Nice to have: Experience with real-time or low-latency serving layers (such as Redis, DynamoDB, or equivalent); while the current system is batch-based, session-level adaptation is a future direction.

• Background in experimentation frameworks for ML systems, including online evaluation of recommendation algorithms (A/B tests, interleaving, counterfactual evaluation).

🏝️ 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 continue learning and growing with us.

• Remote-Friendly: Work from your most productive environment, whether that’s from home or our offices in Madrid, anywhere within a 2-hour difference from Spain (GMT+1).

• Stock Options: Your contributions matter! You will receive stock options, providing you with 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, as comfort fuels creativity!

• Meal Allowances: Receive €60/month on your Cobee card to enjoy meals at restaurants or for food delivery, because good food enhances everything!

• Flexible Compensation: Easily manage your meal, transport, and childcare expenses with Cobee, integrating them directly into your payroll.

• Health Insurance: Access private health coverage at exclusive rates through Adeslas, conveniently deducted from your payroll, ensuring 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 require a visa to work in the EU, we will manage the process and cover the costs to ensure a smooth transition.

• Company events: Yes! We are a fully remote team spread across various countries, but we love to gather periodically in different locations in Spain for team retreats and to recharge at our incredible off-sites!