Python & MLOps Engineer

What we expect in general:

• Strong track record in writing high-quality Python code.
• Hands-on experience with implementing different stages of the Machine Learning Lifecycle.
• Experience with Infrastructure as Code to set up Cloud resources.
• Experience with creating data pipelines (ideally with PySpark).
• Solid understanding of the importance of monitoring in production systems.
• Good command of English (B2/C1).
• Availability to work in a hybrid model from time to time.

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!

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

Driving business innovation through production-ready machine learning pipelines. Collaboration focuses on deploying and maintaining ML workflows while leveraging Azure for cloud computing and on-prem clusters for ETLs. The scope of services involves close cooperation with Data Scientists, active contribution to AI-powered projects, and consulting on technical solutions and translating complex details for business stakeholders. Business delivery is achieved through the independent deployment and monitoring of models in production, combined with building and maintaining analytical dashboards for continuous insights. Furthermore, the engagement encompasses driving technical excellence across the project environment by fostering knowledge sharing and delivering high-level technical sessions.

Pricing team

Project Scope

Delivering price optimisation solutions in close cooperation with a major UK retailer’s data science team. The project aims to enable quick exploration and productionisation of the ML models and respective optimisation algorithms in a hybrid-cloud environment. The ultimate objective is providing APIs for the optimiser to solve pricing class problems across multiple business domains.

Tech Stack

Python (PySpark, Airflow, Azure SDK, fastapi, mlflow), Spark on K8S, Azure ML and IaC with Terraform, CI/CD with GitHub Actions, Docker, Splunk.

Challenges

Addressing numerous pricing problems in the global retailer world sharing similar structures and constraints. The focus is on building robust solutions reusable across multiple domains, leveraging a hybrid on-prem and cloud infrastructure, and ensuring top quality while maintaining quick iterations.

Project Environment

The project delivery involves a core engineering team of 5-7 professionals in Poland, collaborating closely with the client’s product management, data science team, and internal 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
  

,[Implementing the end-to-end Machine Learning Lifecycle, starting from data preparation through automated deployment to continuous monitoring of data and models in production., Developing PySpark data pipelines to load and transform large amounts of data to produce significant features used in modelling and analytics., Provisioning all cloud resources supporting model development in AzureML with IaC using Terraform, Selecting the best architectural patterns to solve business problems., Building robust and maintainable code in the cloud and on-prem to bring models fast and reliably to production, Establishing a mature DevOps culture and developing solutions reusable in multiple business domains.] Requirements: Python, Machine learning, Machine Learning, Infrastructure as Code, Cloud Additionally: Sport subscription, Training budget, Private healthcare, International projects.