Python Engineer with MLOps (Senior) Poland : Kraków + Remote 140 – 170 PLN NET PER HOUR B2B Python Engineer with MLOps (Senior)

Virtuslab Ltd.; Kraków; Hybrid; PLN 180,000 - 300,000; Full time

Benefits offered by this job

Home office reimbursement

Training Package

Virtusity / in-house training

Job summary

VirtusLab Ltd. is seeking an ML Engineer to design and productionize ML pipelines on Azure and on-prem ETL clusters, working closely with Data Scientists to deliver AI-driven solutions and strengthen internal engineering standards.

You will apply Python, PySpark, Kubernetes, and Airflow, with IaC and GitHub Actions integration, in a mostly remote setting with occasional on-site collaboration.

Qualifications

• Experience building production-ready ML pipelines in Python.
• Strong Python expertise and hands-on with PySpark.
• Cloud experience with Azure preferably and IaC practices.
• Familiarity with Kubernetes, Airflow, and GitHub Actions.

Responsibilities

• Develop libraries, tools, and reusable components for ML model deployment and monitoring.
• Collaborate with Data Scientists to productionize ML workflows on Azure and on-prem clusters.
• Contribute to engineering standards and best practices for reliability and scalability.

Job description

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.

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

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).
• Utilising 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 optimise core workflows.
• Fostering industry best practices in code quality, security, and scalability.
• Autonomous, data-driven technical decision-making aimed at driving business growth.
• 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 containerisation.
• 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 us

• Building tech community
• Home office reimbursement
• Training Package
• Virtusity / in-house training

Access to the above perks is optional and completely voluntary for B2B contractors