As part of our team, you will take on the following responsibilities: You are the driving force that transforms innovative AI/ML concepts from the lab environment into robust, scalable products — ensuring prototypes evolve into stable, production‑ready systems.You operationalize the entire ML lifecycle, developing automated CI/CD pipelines, taking ownership of deploying models into production, and continuously expanding our resilient MLOps infrastructure.You implement algorithms and complex feature transformations efficiently within production systems, optimizing them for latency, throughput, and maximum stability.You build scalable data pipelines and feature stores that ensure reliable, consistent data supply for both training and serving — online and offline.You establish professional monitoring mechanisms such as drift detection, automated retraining, and validation processes to guarantee long‑term model quality in live operations.You collaborate closely with Data Scientists, MLOps teams, and IT Infrastructure teams, ensuring that all production‑grade AI/ML solutions follow software engineering best practices and comply with security, privacy, and regulatory requirements. What makes you stand out You hold a master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.You have at least 3 years of professional experience in ML Engineering or MLOps, with a proven track record of building, deploying, and operating tailored AI/ML solutions in production.You bring deep expertise in Python and SQL, hands‑on experience with cloud platforms (ideally Azure), and familiarity with data warehouses such as Snowflake; foundational knowledge of Infrastructure‑as‑Code tools like Terraform is a plus.You are proficient with CI/CD tools (e.g., Azure DevOps), containerization technologies (Docker/Kubernetes), and apply modern software design patterns confidently.You thrive in a dynamic, agile, and innovative environment, working effectively both independently and as part of a team.You possess excellent English communication skills, both written and spoken; German language skills are considered a plus.
What makes you stand out You hold a Bachelor's or Master's degree in Computer Science, IT, or a comparable technical qualification.You bring solid professional experience in cloud engineering – especially with Kafka and Kubernetes.You ideally have relevant certifications in cloud technologies or cloud architecture.You communicate clearly, proactively, and with strong structure – both in technical discussions and in cross‑team collaboration.You can explain complex technical topics in an understandable way, promote active knowledge sharing, and support others with an open and cooperative mindset.You have very good English skills; German is an advantage but not essential.
What makes you stand out Required Qualifications: You hold a degree in Computer Science or a related field and have 3+ years of experience in agile software development, with knowledge of the full engineering lifecycle.You have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MCP servers, agentic AI, and other advanced AI solutions, including practical experience in building and deploying such systems.You are familiar with AI cloud platforms such as Azure AI Foundry and/or conversational AI platforms (e.g., Cognigy), have hands-on DevOps skills ideally in the Azure Cloud (ADO), and bring basic knowledge of cloud technologies, preferably Microsoft Azure.You are familiar with programming fundamentals in at least one high‑level language such as Python, Java, or TypeScript, ideally developing microservices using frameworks such as Flask, Django, or Spring (Java).You communicate clearly and effectively in English and German.
What makes you stand out You hold a Master’s degree in Economics, Mathematics, Statistics, Computer Science, or another related quantitative field.You bring at least 3 years of professional Data Science experience and have a proven track record of bringing models from the lab into real‑world production use cases.You are proficient in Python and SQL and have hands‑on experience building solutions on Azure and working with Snowflake.You have a deep understanding of statistical methods and apply them effectively in an agile, fast‑paced environment.You think in products, not experiments – model versioning, testing, and performance monitoring are second nature to you.You communicate complex topics clearly and with impact, presenting to different audiences confidently; you are fluent in English, and German skills are a plus.