Python/ Machine Learning Engineer (Regular/Senior) @ VirtusLab

Popis pozice

O pozici / o projektu

Původní popisek. 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

You will be responsible for building and owning data pipelines on a Spark Kubernetes cluster orchestrated with Airflow using PySpark. You will improve and introduce data validation and monitoring to ensure trustworthy data at every stage. Tasks will include provisioning and managing Azure resources using a mature Infrastructure as Code approach, as well as automating everything with GitHub Actions and maintaining CI/CD workflows. You will enhance monitoring to further improve the reliability and stability of deployed ML solutions using the Grafana/Prometheus stack. Additionally, you will collaborate with cross functional teams to ensure the seamless deployment and serving of ML models and actively shape the project’s technical roadmap and direction.

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

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!

Detail pracovní nabídky

• ▪Online nábor
• ▪Jazyk náboru: Polština
• ▪Ihned
• ▪Práce plně na dálku
• ▪Pevná pracovní doba

Výhody

• ▪Building tech community
• ▪Flexible hybrid work model
• ▪Home office reimbursement
• ▪Language lessons
• ▪MyBenefit points
• ▪Training Package
• ▪Virtusity / in-house training

O firmě