Full stack engineer

European Tech Recruit; A distancia; EUR 38.000 - 60.000; Jornada completa

Descripción de la vacante

Una plataforma de programación de citas en línea busca un Ingeniero Full Stack para trabajar de forma completamente remota en España o Polonia. El candidato ideal tendrá experiencia en la entrega de componentes de IA, habilidades fuertes en Python y un profundo conocimiento de los marcos de ML. Las responsabilidades incluyen diseñar y desarrollar sistemas de IA de producción, crear tuberías escalables y mantener la calidad de los datos. Se ofrece la oportunidad de trabajar en un entorno innovador y colaborativo.

Formación

• Experiencia en la entrega de componentes de IA completos, desde la planificación hasta el monitoreo.
• Fuerte familiaridad con marcos de aprendizaje automático.
• Experiencia prácticas con herramientas MLOps y nubes de datos.

Responsabilidades

• Diseñar sistemas de IA de producción confiables y listos para el uso.
• Preparar conjuntos de datos de alta calidad y mantener almacenes de características.
• Desarrollar tuberías de datos y ML de extremo a extremo.

Conocimientos

Experiencia en Python

Experiencia con ML frameworks (Scikit-Learn, Tensor Flow, Py Torch, Hugging Face)

Experiencia con herramientas MLOps (MLflow, Zen ML)

Experiencia con Airflow

Conocimiento en Kafka y Spark

Evaluación de modelos

Descripción del empleo

Full Stack Engineer

Recuerde revisar su CV antes de enviar la solicitud. Además, asegúrese de leer todos los requisitos relacionados con este puesto.

Fully Remote in Spain or Poland

We are working with a leading online scheduling platform designed to simplify the process of coordinating meetings and events. Founded over 18 years ago, it helps individuals and teams avoid the "back-and-forth" of email scheduling by allowing users to propose multiple time slots and let participants vote on their availability.

Responsibilities of the role

• Architect Production AI Systems : Design reliable, production‑ready AI systems, selecting optimal tools for robust real‑world performance.
• Curate Data & Feature Stores : Prepare high‑quality datasets and maintain feature stores to ensure data consistency for training and inference.
• Build Scalable ML Pipelines : Develop end‑to‑end data and ML pipelines using Airflow and dbt for seamless ingestion, deployment, and monitoring.
• Design & Deploy Models : Prototype and train diverse neural architectures, including LLMs, with a focus on reproducibility and performance.
• Implement Advanced Retrieval (RAG) : Design Graph RAG and hybrid retrieval systems, including graph construction and entity linking.
• Enable Edge Intelligence : Optimize and quantize large models for efficient on‑device and edge processing.

Requirements of the role

• Experience delivering complete AI components—from planning and modeling to deployment, monitoring, and iteration.
• Strong Python skills and deep familiarity with ML frameworks such as Scikit‑Learn, Tensor Flow, Py Torch, and Hugging Face. You're comfortable designing, evaluating, and prototyping diverse model types.
• Hands‑on experience with MLOps tools (e.g., MLflow, Zen ML), dbt modeling, and working with cloud data warehouses or data lakes.
• Experience building and scheduling pipelines in Airflow. Familiarity with modern data stacks such as Kafka, Spark, and cloud warehouses (Big Query, Redshift, Snowflake). Ability to define event‑level tracking schemas for reliable analytics.
• Strong understanding of model behavior and evaluation. Experience developing frameworks for assessing model quality, reliability, hallucination detection, prompt regression, safety scoring, or multi‑hop reasoning. Familiarity with RAG, graph‑based retrieval, and prompt design.
• A focus on shipping systems that are robust, explainable, and usable by others.