Machine Learning Engineer (Azure)

We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization.

About the role

Join our team to drive business innovation with production-ready machine learning pipelines. You will play a key role in deploying and maintaining ML workflows, leveraging Azure for cloud computing and on-prem clusters for ETLs. Collaborating closely with Data Scientists, you will contribute to AI-powered projects while shaping the organization’s technical culture.

Python: Expert

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

Project

Forecasting & Commodities

Project Scope

As an ML Engineer in Forecasting and Commodities, you will be involved in projects that support critical decision making processes, by applying your Python, PySpark, Kubernetes and Cloud (Azure) skills. You will be working in a technically mature ecosystem, implementing new features and covering new use-cases. Part of your responsibilities will be design and implementation of a data science innovation framework, as well making contributions to an overall engineering best practises of the organization.

Responsibilities

– Developing libraries, tools, and frameworks that standardise and accelerate development and deployment of machine learning models.

– Working in an Azure cloud environment, developing model training code in AzureML. Building and maintaining cloud infrastructure with IaC (infrastructure as code).

– 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.

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 a system that provides accurate and up-to-date business forecasts, by providing a set of tools that can be easily leveraged by data scientists and analysts.

– Streamlining the process of onboarding, deployment and patching new ML pipelines.

– Collaborating with cross-functional teams enhancing customer experiences through innovative technologies.

– Employing DevOps practises for reproducible patterns in multiple business domains.

Team

1 engineer from VL, two from client side

What we expect in general:

• The ability to work in hybrid model from Krakow office is a must (1 day per month).

• Hands-on experience in deploying Python projects.

• Strong experience in writing high-quality Python code.

• Experience with orchestration tools such as Airflow.

• Knowledge of Spark or other distributed data processing tools.

• Experience with Kubernetes ecosystem as a user.

• Strong experience in Azure and Docker

• Ability to work in a team and participate in the design process.

• Good command of English (B2/C1).

• Strong communicator

• Team player with mentoring ability

• Proactive and responsible

• Strategic thinker with big-picture perspective

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

And a lot more!