AI Engineer (Full Remote)

At Gstock, we have been revolutionizing restaurant and hotel management since 2013. Our web application, specifically designed for the HORECA sector, has earned the trust of thousands of establishments looking to optimize their operations and maximize profitability.

We are passionate about what we do and proud of the positive impact we have on our clients. With energy and enthusiasm, we head into 2026 as a key year for our large-scale expansion.

Gstock joined Everfield in 2024. The team is based Madrid, Spain.

We are seeking a proactive tech enthusiast with the ability to work autonomously to lead our AI & Data department.

• Degree in Computer Science, Mathematics, or similar.

• At least 3 years of experience in this role or as a Data Scientist.

• Ability to understand processes and identify optimization opportunities.

• Knowledge of optimization techniques, model evaluation, and performance metrics.

• Solid experience in Traditional Machine Learning.

• Experience in demand forecasting within the retail/hospitality sector.

• Experience working with Big Data (massive datasets).

• Ability to identify patterns, trends, and opportunities through data.

• Strong reading and writing skills in English and Spanish.

• A professional capable of working independently as the sole lead for the AI & Data area.

• Developing and applying models and algorithms.

• Training, validating, and optimizing Machine Learning and Deep Learning models.

• Integrating Generative AI and LLMs into various solutions.

• Documentation, versioning, and maintenance of models.

• Developing, maintaining, and optimizing high-quality, reliable, and robust data pipelines.

• Extraction, cleaning, and validation of large datasets.

• Data interpretation to uncover solutions and business opportunities.

• Data analytics using Business Intelligence tools such as Apache Superset.

• Solid foundation in mathematics and statistics.

• Expert knowledge of machine learning models and analytical/mathematical modeling.

• Statistical knowledge of Time Series and forecasting evaluation metrics.

• Advanced proficiency in Python (OOP best practices, testing, Pandas, PySpark, NumPy,

Scikit-learn, LightGBM / XGBoost / Catboost, Matplotlib, TensorFlow, Hugging Face).

• Graph analysis and algorithm development.

• Knowledge of the state-of-the-art in Language Models and GenAI.

• Agentic AI Architecture: agent loops, tools, MCPs, and Python agentic libraries.

• Ability to deploy agents, build RAG systems, and extraction techniques using

visual/computer vision models.

• Strong mastery of SQL and query optimization.

• Knowledge of the Big Data ecosystem (Spark, Glue, Redshift, etc.).

• Airflow: Ability to build DAGs to orchestrate data flows.

• Experience handling Big Data file formats such as Parquet and DuckDB.

• Pipeline design and ETL architecture (scheduling, backfilling management, fault recovery,

etc.).

• Knowledge of AWS and basic data infrastructure (S3, Redshift, Bedrock, EC2, EKS, ECR).

• Docker: Containerization for service deployment.

• Kubernetes: Ability to operate and interact with clusters.

• Scalable architectures for ML operations.

• Proficiency with GIT version control.

• Experience putting models into production.

• Continuous monitoring and model retraining for live operations.

• Knowledge of data visualization tools (Apache Superset, Power BI).

• Dashboarding: Ability to create dashboards for business stakeholders.