Über
Design and implement scalable backend services and microservices powering data-intensive, real-world applications Build and deploy production ML models across the full lifecycle from feature engineering and training through evaluation, deployment, and monitoring Develop and maintain event-driven distributed pipelines using Apache Kafka, Apache Spark, and related technologies Architect systems that integrate ML models with rule-based decision engines for automated, real-time decisioning Collaborate across disciplines to translate complex requirements into reliable, elegant engineering solutions Contribute to AI/LLM-driven workflows and orchestration systems that push the boundaries of what software can do Required Experience/Knowledge:
M.S. in Computer Science, AI, or a related field 6+ years in backend software engineering and distributed systems Strong proficiency in Java (Spring Boot, Spring MVC, Hibernate) and Python Hands-on experience building and deploying production ML models (PyTorch or equivalent) Experience with distributed systems and streaming technologies: Apache Kafka, Apache Spark, ZooKeeper Solid understanding of microservices architecture, REST/SOAP APIs, and object-oriented design Experience with relational and NoSQL databases (Oracle, IBM Db2, MSSQL, MongoDB) Familiarity with AWS or equivalent cloud platforms Strong problem-solving skills Intrinsic drive to understand how things work and make them better Excellent communicating and collaboration across engineering, data, and product teams
Sprachkenntnisse
- English
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