Machine Learning Engineer (Recommendations) (EdTech)

TL;DR

Machine Learning Engineer (Recommendations) (EdTech): Building and optimizing recommendation infrastructure and exploring advanced ML algorithms to personalize educational content for millions of users with an accent on scalability, production-readiness, and low-latency serving. Focus on developing deep learning-based models, contextual bandits, and robust ML pipelines on AWS.

Location: Remote, but must be within a 2-hour time difference from Spain (GMT+1)

Company

Global leader in educational technology specializing in a "Playlearning" approach to help families raise children through interactive learning experiences.

What you will do

• Own and optimize production recommendation infrastructure to ensure reliability, low latency, and scalability.
• Research and prototype advanced algorithms, including deep learning, contextual bandits, and graph-based methods.
• Develop production-grade ML models and monitored pipelines integrated into the live recommendation engine.
• Design scalable serving layers, caching strategies, and pipeline orchestration to handle growing catalogs and traffic.
• Build and maintain data pipelines in DBT and Databricks for clean transformations and experimentation frameworks.
• Monitor model health in production, detect drift, and define retraining strategies.

Requirements

• Strong Python skills for producing testable, version-controlled ML code and infrastructure.
• Proficiency in SQL and hands-on experience with DBT for reliable transformation pipelines.
• Experience deploying and monitoring ML models using AWS services (SageMaker, Lambda, ECS, Step Functions).
• Ability to design and maintain scalable batch ML training and evaluation pipelines.
• Familiarity with advanced recommendation techniques like two-tower models and transformers.
• Fluency in English (spoken and written) is essential.

Nice to have

• Experience with low-latency serving layers such as Redis or DynamoDB.
• Knowledge of ML experimentation frameworks, including A/B tests and counterfactual evaluation.
• Experience with modern data stack tools like Snowflake, BigQuery, or Fivetran.
• Exposure to knowledge graph or content graph approaches for content-aware recommendations.

Culture & Benefits

• Annual learning budget of €2,000 for books and training.
• Home office allowance of €400 plus €35 monthly remote work expense.
• Stock options to share in the company's success.
• Private health insurance and free language classes in Spanish and English.
• Visa sponsorship for the EU is provided and costs are covered.
• Regular team gatherings and off-sites in Spain.