Key skills
AWSAzureCloudGoogle Cloud PlatformNoSQLNumpyPandasPythonScikit-LearnSQLRAIMLGenerative AIscikit-learnNumPySnowflakeBigQueryDatabricksGCPGoogle CloudSageMakerVertex AIGit
About this role
Role Overview
- Manage the entire journey of an AI solution, from initial problem-solving and data cleaning to building production-ready systems
- Implement a wide range of algorithms—from traditional statistical optimization and predictive modeling (supervised/unsupervised) to advanced Generative AI using LLMs and Transformers
- Transition models from local environments to the cloud using an engineering mindset
- Work across the "Big Three" (AWS, GCP, and Azure) and leverage specialized platforms like Databricks, SageMaker, and Vertex AI to handle large-scale data science needs
- Translate complex datasets into actionable business insights
- Collaborate with Data Engineers to integrate models into live systems
Requirements
- Master’s degree in a STEM field (Computer Science, Engineering, Mathematics, Statistics, Data Science, or related)
- Recent graduates are welcome, even with limited professional experience
- Proficiency in R, Python and its ecosystem (NumPy, Pandas, scikit-learn)
- Familiarity with Git, virtual environments, and SQL/NoSQL databases
- Understanding of core ML concepts (regression, classification, clustering, dimensionality reduction)
- English at a B2 level (this will be tested during the interview)
- Spanish is a plus
Tech Stack
- AWS
- Azure
- Cloud
- Google Cloud Platform
- NoSQL
- Numpy
- Pandas
- Python
- Scikit-Learn
- SQL
Benefits
- Access our Internal Academies for 80 hours of initial training
- Ongoing coaching and support for top-tier certifications (AWS, Snowflake, Google BigQuery, etc.)
- Semi-annual performance reviews to discuss your achievements, new challenges, and salary adjustments based on your results
- Financial support for your home office
- Opportunities for international travel