Описание Parser is a general leader in the travel industry. Its Machine Learning Engineering team builds ML solutions for ranking, recommendation, and pricing optimization. Задачи * Design and implement scalable ML infrastructure for training, deployment, and serving in batch and real-time environments * Build and maintain efficient data pipelines for large-scale processing and feature engineering * Optimize compute resources and improve model-serving performance across ML systems * Implement monitoring, logging, and alerting systems, and contribute to ML Ops practices, including CI/CD pipelines * Collaborate with data scientists to streamline the model development-to-production workflow * Research and integrate new technologies * Mentor junior engineers and communicate technical solutions to diverse stakeholders Требования * Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field * 6–7 Years of experience in Software, Data, or ML engineering roles (preferred)



* Strong problem-solving skills * Proficiency in Java; Python is desirable * Understanding of ML algorithms and model architectures * Experience building scalable, reliable ML systems * Exposure to cloud platforms such as AWS, containerization with Docker, and scalable data systems such as Spark and Kafka * Familiarity with CI/CD tools such as GitHub Actions and ML model serving technologies such as MLflow * Ability to collaborate well across teams * A solid foundation in at least one of software engineering, data engineering, distributed systems, or applied machine learning, and readiness to grow into other areas as required * Будет плюсом: Python Условия A friendly, collaborative team focused on knowledge sharing and continuous learning Opportunity to work on MLOps and Machine Learning infrastructure using Java, Python, AWS, Docker, Kafka, Spark, and MLflow to power real-time ML systems #J-18808-Ljbffr

📌 backend engineer with MLOps for travel ML systems (Comunidad de Madrid)
🏢 Parser
📍 Comunidad de Madrid