Informacje o stanowisku

We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities, and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! 

Project scope
As an ML Engineer in StoreOps, you will dive into projects that streamlining retail operations through the use of analytics and ML, by applying your Python, Spark, Kubernetes, and Cloud (Azure) skills. You will be contributing to a mix of mature and new projects by bringing machine learning pipelines into production, as well as fostering a technical culture of the organization.

Challenges
- Enhancing the monitoring, reliability, and stability of deployed solutions, including the development of automated testing suites.
- Automating the machine learning model lifecycle to continuously improve the performance on production.
- Collaborating with cross-functional teams enhancing customer experiences through innovative technologies.

Tech stack

Python, PySpark, Airflow, Docker, Kubernetes, Dask, xgboost, pandas, scikit-learn, numpy, GitHub Actions, Azure DevOps, Terraform, Git @ GitHub

Team

5 engineers

• The ability to work in hybrid model from Krakow office is a must (3 days per week).
• Hands-on experience in deploying Python projects.
• Strong experience in writing high-quality Python code.
• Experience in developing CI/CD components and a good understanding of the SDLC.
• Experience with orchestration tools such as Airflow.
• Knowledge of Spark or other distributed data processing tools.
• Experience with Kubernetes ecosystem as a user.
• Experience with IaC, particularly Terraform, is a plus.
• Experience with Azure is a plus.
• Ability to work in a team and participate in the design process.
• Good command of English (B2/C1).

We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities, and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! 

Project scope
As an ML Engineer in StoreOps, you will dive into projects that streamlining retail operations through the use of analytics and ML, by applying your Python, Spark, Kubernetes, and Cloud (Azure) skills. You will be contributing to a mix of mature and new projects by bringing machine learning pipelines into production, as well as fostering a technical culture of the organization.

Challenges
- Enhancing the monitoring, reliability, and stability of deployed solutions, including the development of automated testing suites.
- Automating the machine learning model lifecycle to continuously improve the performance on production.
- Collaborating with cross-functional teams enhancing customer experiences through innovative technologies.

Tech stack

Python, PySpark, Airflow, Docker, Kubernetes, Dask, xgboost, pandas, scikit-learn, numpy, GitHub Actions, Azure DevOps, Terraform, Git @ GitHub

Team

5 engineers

,[Developing machine learning models and feature engineering pipelines with cooperation with data scientists., Working with distributed data processing tools such as Spark, to parallelise computation for Machine Learning., Diagnosing and resolving technical issues, ensuring availability of high-quality solutions that can be adapted and reused., Collaborating closely with different engineering and data science teams, providing advice and technical guidance to streamline daily work., Championing best practices in code quality, security, and scalability by leading by example., Taking your own, informed decisions moving a business forward. Requirements: Python, Airflow, CI/CD, Spark, Kubernetes, AzureML, ML, Docker, Terraform Additionally: Building tech community, Home office reimbursement, Language lessons, MyBenefit points, Private healthcare, Stretching, Training Package, Virtusity / in-house training, Free coffee, Bike parking, No dress code, Shower, Free snacks, Free beverages, Modern office, Kitchen.

Praca Kraków

Kraków - Oferty pracy w okolicznych lokalizacjach