Python Engineer with MLOps (Senior)
VirtusLab is a leading European software consulting and engineering company. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering professionals to make a substantial impact in the software industry.
An opportunity to drive business innovation through robust, production-ready machine learning pipelines. The main focus involves deploying and maintaining ML workflows across Azure cloud infrastructure and on-prem ETL clusters. The role centers on technical collaboration with Data Scientists to build AI-driven solutions and refine internal engineering standards.
Project Scope
The ML Engineer / Forecasting & Commodities engagement covers key initiatives supporting critical decision-making processes through the application of Python, PySpark, Kubernetes, and Azure Cloud technology stacks. The scope involves operating within a highly mature technical ecosystem, delivering new features, and scaling solutions to encompass advanced use cases. Key project focus areas include designing and implementing a data science innovation framework while contributing to the organization’s overarching engineering best practices.
Tech Stack
Python, PySpark, Airflow, Docker, Kubernetes, Azure (incl. Azure ML), pandas, scikit-learn, numpy, GitHub Actions, Azure DevOps, Terraform, Git @ GitHub
Project Challenges
– Building high-accuracy business forecasting systems by delivering reusable toolsets tailored for data scientists and analysts. – Streamlining onboarding, deployment, and automated patching pipelines for new ML models. – Partnering with cross-functional units to enhance end-customer experience through cutting-edge technology integration. – Applying robust DevOps methodologies to establish reproducible patterns across multiple business domains.
Team
3 engineers
A few perks of being with us
Building tech community
Flexible hybrid work model
Home office reimbursement
Language lessons
MyBenefit points
Private healthcare
Training Package
Virtusity / in-house training
Access to the above perks is optional and completely voluntary for B2B contractors
Daily tasks
- Developing libraries, tools, and frameworks to standardise and accelerate the end-to-end development and deployment of machine learning models.
- Operating within an Azure cloud environment, including developing model training code in AzureML and building/maintaining cloud infrastructure via Infrastructure as Code (IaC).
- Utilizing distributed data processing tools such as Spark to parallelise machine learning computations across large-scale datasets.
- Diagnosing and resolving technical issues, ensuring the delivery of high-availability, reusable, and adaptable engineering solutions.
- Collaborating with cross-functional engineering and data science teams to deliver technical guidance and optimize core workflows.
- Fostering industry best practices in code quality, security, and scalability.
- Autonomous, data-driven technical decision-making aimed at driving business growth.
Requirements
- Solid Python skills with hands-on experience taking projects to production.
- Practical experience with orchestration tools such as Airflow.
- Background in distributed data processing, especially Spark.
- Hands-on experience with Kubernetes.
- Cloud experience (Azure preferred) and Docker containerization.
- Smooth collaboration with cross-functional teams and hands-on involvement in technical design.
- Clear and direct communication with both tech and business partner.
- Readiness to share domain expertise and support other team members in technical growth.
- High level of independence, pragmatic problem-solving, and a clear big-picture view.
- English language proficiency at a minimum [B2/C1] level.
- Primarily remote-based engagement with occasional on-site collaboration in Kraków (approx. once a month).
Must have: Python, Airflow, Spark, Kubernetes, Cloud, Azure, Docker
Nice to have: MLOps