Python/ ML Engineer (Regular/Senior)

O projekcie: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be responsible for building and owning data pipelines on a Spark Kubernetes cluster orchestrated with Airflow using PySpark. You will improve and introduce data validation and monitoring to ensure trustworthy data at every stage. Tasks will include provisioning and managing Azure resources using a mature Infrastructure as Code approach, as well as automating everything with GitHub Actions and maintaining CI/CD workflows. You will enhance monitoring to further improve the reliability and stability of deployed ML solutions using the Grafana/Prometheus stack. Additionally, you will collaborate with cross functional teams to ensure the seamless deployment and serving of ML models and actively shape the project’s technical roadmap and direction. Project Loss Prevention Project Scope Loss prevention in retail involves the strategic implementation of processes and technologies designed to identify, mitigate, and prevent the disappearance of inventory. To achieve that an Engineering and a Data Science team within a major UK retailer partner to bridge the gap between experimental ML models and robust, production-grade systems. By embedding engineering excellence into the data science lifecycle, the team ensures that loss prevention insights are delivered with high reliability. In this project you will not only develop high-quality Python code, but also implement trustworthy data pipelines on a big Spark cluster orchestrated with Airflow, setup highly automated CI/CD pipelines with Github Actions, and provision Azure infrastructure as code with Terraform. Tech Stack Python, PySpark, Airflow Azure, IaC (Terraform), CI/CD (Github Actions), Observability (Grafana/Promotheus), MLOps, Kubernetes Team 3 Engineers A few perks of being with us - Flexible hybrid work model - Home office reimbursement - Language lessons - MyBenefit points - Private healthcare - Training Package - Virtusity / in-house training Wymagania: What we expect in general: - Strong experience in writing high-quality Python code and deploying production-level projects. - Proactiveness and a strong sense of ownership, taking full responsibility of project outcomes. - Significant experience in Data Engineering, specifically with PySpark, data quality monitoring and workflow orchestration. - Proficiency in Azure (or equivalent cloud providers) and hands-on experience with Infrastructure as Code principles. - Robust DevOps mindset with practical experience automating CI/CD pipelines via GitHub Actions. - A dedicated team player with excellent communication skills who thrives within a cross-functional, collaborative environment. - Good command of English (B2/C1 level), comfortable utilizing the language daily. - A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! Codzienne zadania: - Establish a resilient MLOps Ecosystem by integrating robust observability, experiment tracking and automated deployment to model serving infrastructure. - Improve the reliability and observability of data pipelines to guarantee trust-worthy data. - Advancing DevOps Maturity through the implementation of standardized pipelines, enabling rapid iteration and minimizing manual intervention.