Everfield
AI Engineer
EverfieldSpain3 days ago
Full-timeRemote FriendlyEngineering, Information Technology
About Everfield

Everfield buys, builds, and grows European vertical market and specialist software companies, providing them with the tools they need to move to the next level. Our mission is to foster ambition, fuel growth, and unlock opportunities for Europe’s software ecosystem.

Companies in the Everfield ecosystem follow a decentralised model, maintaining their team, brand, and offices, while focusing on what they do best - building products and supporting customers. Everfield provides support in talent acquisition, HR, and a team of experts in building and growing European B2B SaaS companies consult on financial and operational topics from. Founded in 2022, Everfield has an ecosystem presence in 7 countries, and growing.

About Gstock

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.

What are we looking for?

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

What will your responsibilities be?

  • 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.

Technical Requirements

Data Science & Machine Learning

  • 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.

Generative AI

  • 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.

Data Engineering & Big Data

  • 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.).

Infrastructure & Operations (MLOps)

  • 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.

Business Intelligence

  • Knowledge of data visualization tools (Apache Superset, Power BI).
  • Dashboarding: Ability to create dashboards for business stakeholders.

What do we offer?

  • 100% Remote work.
  • Flexible schedule: Daily stand-up at 08:30 AM with core hours until 02:00 PM; you

manage the rest of your day.

  • Competitive salary.
  • Great working environment.

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