04.10.2026 | Pełny etat | Gdańsk (Gdańsk) | CycladWill work across the full technology stack, developing backend services and APIs using Python and modern frontend applications using React. You will contribute to transforming exploratory Proof-of-Concepts developed by Data Scientists into robust, scalable, production-ready solutions while working
Zobacz później04.10.2026 | Pełny etat | Kraków | CycladAnd coverage strategies for highly configurable IP using Python and C+, with support for different RTL simulation environments and EDA platforms. Maintain, optimize, and extend existing verification workflows and infrastructure. Improve verification metrics, increase automation, and identify opportunities
Zobacz później03.10.2026 | Pełny etat | Wrocław | CycladInto data solutions Support production environments, handle incident analysis, and contribute to performance optimization Ensure compliance with data governance, security, and regulatory standards Competence demands 3-5 YoE in Data Engineering with Databricks Very strong Python, SQL, PySpark programming
Zobacz później03.10.2026 | Pełny etat | Wrocław | CycladDatabricks and Azure Data Factory pipelines Write complex SQL queries to perform data analysis, validation, and defect investigation Use Python to automate data testing, validation, comparison, and reporting activities Perform source-to-target data validation and ensure data integrity across systems Support
Zobacz później03.10.2026 | Pełny etat | Warszawa | CycladAnd maintain scalable backend applications using Python and FastAPI while working with AWS cloud services, ETL pipelines, Docker, and CI/CD practices. You will also contribute to AI/LLM-based applications, including RAG solutions, document analysis platforms, and chat interfaces, while collaborating
Zobacz później03.10.2026 | Pełny etat | Gdańsk (Gdańsk) | CycladEnvironments Building scalable software components and services integrating ML models Developing and maintaining applications and APIs using Python Implementing the complete ML lifecycle data preparation, model development, evaluation, deployment and monitoring Productionizing Machine Learning models
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