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.

About the role

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.

Primarily remote-based engagement with occasional on-site collaboration (approx. once a month).

• Python: Advanced
• Cloud (prefered Azure): Advanced
• IaC: Regular
• GitHub Actions: Advanced
• Pyspark: Regular
• Airflow: Regular
• Experience with observability: Nice to have
• MLOps: Proven ability to productionize models and set up monitoring: Nice to have
• Productionize models and set up monitoring: Regular
• Kubernetes: Nice to have
• English: Advanced

View available projects

Project

Forecasting & Commodities

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.

Key Scope of Services

– 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.

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

What we expect in general:

• 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 (approx. once a month).

A few perks of being with usBuilding 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