backend engineer with MLOps for travel ML systems
Hace 2 días
madrid, comunidad de madrid, España
Parser
Jornada completa
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ОписаниеParser is a global leader in the travel industry. Its Machine Learning Engineering team builds ML solutions for ranking, recommendation, and pricing optimization.ЗадачиDesign and implement scalable ML infrastructure for training, deployment, and serving in batch and real-time environmentsBuild and maintain efficient data pipelines for large-scale processing and feature engineeringOptimize compute resources and improve model-serving performance across ML systemsImplement monitoring, logging, and alerting systems, and contribute to ML Ops practices, including CI/CD pipelinesCollaborate with data scientists to streamline the model development-to-production workflowResearch and integrate new technologiesMentor junior engineers and communicate technical solutions to diverse stakeholdersТребованияBachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field6–7 Years of experience in Software, Data, or ML engineering roles (preferred)Strong problem-solving skillsProficiency in Java; Python is desirableUnderstanding of ML algorithms and model architecturesExperience building scalable, reliable ML systemsExposure to cloud platforms such as AWS, containerization with Docker, and scalable data systems such as Spark and KafkaFamiliarity with CI/CD tools such as GitHub Actions and ML model serving technologies such as MLflowAbility to collaborate well across teamsA 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 requiredБудет плюсом: PythonУсловияA friendly, collaborative team focused on knowledge sharing and continuous learningOpportunity to work on MLOps and Machine Learning infrastructure using Java, Python, AWS, Docker, Kafka, Spark, and MLflow to power real-time ML systems