ML / MLOps Engineer

At Grape Up, we transform businesses by unlocking the potential of AI and data through innovative software solutions.We partner with industry leaders in the automotive and aviation to build sophisticated Data & Analytics platforms that support production machine learning and AI use cases. Our solutions provide comprehensive capabilities spanning data storage, management, advanced analytics, machine learning, enabling enterprises to accelerate innovation and make trusted, data-driven decisions. ResponsibilitiesPartner with the Data Science teams to harden experimental code and take it from a sandbox environment into production by applying engineering best practicesDesign, implement and own scalable ML infrastructure and deployment pipelines capable of handling high-volume model training and inference workloadsBuild and maintain automated CI/CD pipelines for ML model development, testing, validation, and deployment, integrating with customer platforms and Databricks environmentsDefine, monitor and continuously improve KPIs covering model performance, data quality, system reliability, deployment velocity, and operational efficiencyEstablish and implement MLOps best practices including experiment tracking, model versioning, feature stores, and governance (e.g. MLflow, Unity Catalog)Optimize ML infrastructure for cost efficiency and performance through automated scaling and resource management RequirementsMaster’s degree in computer science, Machine Learning, Data Engineering, or a related field2+ years of professional experience in ML Engineering, MLOps, or DevOps with a strong focus on production ML systemsStrong Python programming skills and proficiency with ML frameworks (PyTorch, TensorFlow, scikit-learn)Experience across the full ML lifecycle: experiment tracking (e.g. MLFlow), model deployment, and production operationsHands-on experience with ML workflow orchestration and pipeline automationExperience deploying and operating ML systems preferably on cloud platforms (Azure preferred; AWS or GCP also valued)Strong problem-solving skills and ability to work independently in fast-paced environmentsFluency in English, both written and spoken Nice to havePhD degree in Computer Science, Data Engineering, AI, or a related field (completed or in progress)Hands-on experience deploying and managing ML models in Databricks environmentsExperience with containerized ML workloads using Docker and KubernetesExperience implementing model monitoring, observability, and performance trackingKnowledge of feature stores and model versioning best practices Benefits of joining Grape UpNon-corporate work environment among experienced engineersIndividual growth & development plan supported by cyclical feedback sessionsAccess to knowledge platforms (e.g. Pluralsight)Equipment of your choiceFinancing of conferences, external trainings, and certificationsLanguage lessons (English, German and Polish for foreigners) LuxMed private medical careWeekly Lunch & Learn where we meet up in the office, lunch together, and share our knowledgeEmployee referral programRewards for the success of the month and year awarded by our employeesSpecial rewards for your years with us (G-Man)Integration activities