Machine Learning Engineer
⚲ Kraków
23 520 - 31 080 PLN netto (B2B)
Wymagania
- Machine Learning
- Python
- Airflow
- Spark
- Kubernetes
- Azure
- Docker
Opis stanowiska
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
Driving business innovation with production-ready machine learning pipelines. The cooperation involves deploying and maintaining ML workflows, leveraging Azure for cloud computing and on-prem clusters for ETLs. Collaborating with Data Scientists includes contributing to AI-powered projects while shaping the technical culture.
Python ExpertTerraform Advanced
Docker Advanced
Azure Advanced
GitHub Actions Advanced
AzureML, Web Apps , AirFlow Nice to have
Spark Nice to have
Dashboarding / visualization skills Nice to have
Exposure to other programming technologies Nice to have
View available projects
Project
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.
The scope of cooperation covers:
• 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.
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.
Desired competencies & professional profile:
• 5+ years of hands-on machine learning engineering experience.
• Strong proficiency in writing high-quality Python code.
• Experience with orchestration tools such as Airflow.
• Knowledge of Spark or other distributed data processing tools.
• Experience with the Kubernetes ecosystem as a user.
• Advanced expertise in Azure and Docker.
• Capability to collaborate within an engineering team and contribute effectively to the design process.
• Good command of English (B2/C1).
• Strong communication and mentoring capabilities.
• Proactive, responsible approach with a strategic, big-picture perspective.
• 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!
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
About
Driving business innovation with production-ready machine learning pipelines. The cooperation involves deploying and maintaining ML workflows, leveraging Azure for cloud computing and on-prem clusters for ETLs. Collaborating with Data Scientists includes contributing to AI-powered projects while shaping the technical culture.
Python ExpertTerraform Advanced
Docker Advanced
Azure Advanced
GitHub Actions Advanced
AzureML, Web Apps , AirFlow Nice to have
Spark Nice to have
Dashboarding / visualization skills Nice to have
Exposure to other programming technologies Nice to have
View available projects
Project
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.
The scope of cooperation covers:
• 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.
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.
Desired competencies & professional profile:
• 5+ years of hands-on machine learning engineering experience.
• Strong proficiency in writing high-quality Python code.
• Experience with orchestration tools such as Airflow.
• Knowledge of Spark or other distributed data processing tools.
• Experience with the Kubernetes ecosystem as a user.
• Advanced expertise in Azure and Docker.
• Capability to collaborate within an engineering team and contribute effectively to the design process.
• Good command of English (B2/C1).
• Strong communication and mentoring capabilities.
• Proactive, responsible approach with a strategic, big-picture perspective.
• 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!
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
🔍 Dekoder Ogłoszenia
🟢
craft clean code and practical solutions with precision and purpose
Firma kładzie nacisk na jakość kodu i praktyczne podejście, co może oznaczać rygorystyczne standardy kodowania i procesy code review.
🟢
foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency
Kultura firmy opiera się na inżynierii, odpowiedzialności i otwartości, co może sugerować samodzielność w działaniu i możliwość wpływania na projekty.
🟢
empowering professionals to make a substantial impact in the software industry
Firma daje pracownikom możliwość znaczącego wpływu na branżę, co może oznaczać pracę nad innowacyjnymi projektami i możliwość rozwoju.
🟢
Driving business innovation with production-ready machine learning pipelines
Celem jest wdrażanie innowacji biznesowych poprzez gotowe do produkcji potoki uczenia maszynowego, co sugeruje praktyczne zastosowanie ML w realnych scenariuszach.
🟡
The cooperation involves deploying and maintaining ML workflows, leveraging Azure for cloud computing and on-prem clusters for ETLs.
Zakres obowiązków obejmuje zarówno wdrażanie, jak i utrzymanie potoków ML, z wykorzystaniem chmury Azure oraz własnych zasobów (on-prem) do przetwarzania danych.