Machine Learning Engineer (Data & AI, Data Science Team)

We’re always looking for the ones truly passionate about their work. If you are amongst them, you can rest assured there is a place for you in eMAG. We’ve grown very fast and we are determined to keep doing so. What brought us here is our desire for continuous evolution and practical results.

More than 6000 colleagues are part of eMAG Teams. We strongly believe in people development and therefore every year we invest more and more energy and resources to remain an organization that is constantly learning. We want to make sure that you’ll have the most talented colleagues, as well as the proper environment to grow and achieve great results, to become what you desire on a personal and professional level. Join us, grow faster!

Machine Learning Engineer (Data & AI, Data Science Team)

The team in question is responsible with the development, deployment and monitoring ML/AI models that impact different business areas, such as: Content, Marketplace, Operations, Commercial. 

Our role is to provide challenging and suitable projects for data science, infrastructure, data, technologies and to create a safe environment for learning and development. We develop and deploy on-premises and/or on-cloud depending on the project. The trend is towards cloud, development and production, but with yet no deadline. We provide access to Kubernetes cluster with GPU's included, running Docker containers on each task, writing Python and PySpark with internal standards for coding.

What you’ll have to do:

·       As Machine Learning Engineer in our team, your role is to formulate and argument a hypothesis, to access, clean and aggregate data, train and interpret models, present the result, get feedback and deploy model in production. This implies collaboration with the team members involved in the process, others machine learning engineers, team lead, product owner, analysts, clients and data teams. It is part of our values to help other team members or other teams in the process. It is a non-negotiable value for us.

How we’d like you to be:  

·       In order for you to adapt for the role you need to have appropriate skills for data wrangling with SQL and PySPark, for structured and unstructured data (text), good understanding of ML/AI techniques, such as boosting, transformers and LLM's, on top of strong mathematical and statistical background about mentioned techniques and be able to efficiently write Python code for development and production using versioning control system (Git).

·       Familiarity with MLOps tools like Kubernetes, Docker, Kubeflow, will make your work and ours a lot easier.

What we’ve prepared for you:

·       Medical subscription: Medicover, MedLife or Regina Maria.

·       A flexible budget that you can invest in yourself as you wish: meal tickets, holiday tickets, cultural vouchers, private pension, foreign language classes, eMAG, Fashion Days, Tazz, Therme & Genius, membership to different gyms or even professional development classes.

·       Different discounts from our partners: banking, mobile, dental medicine or wellness.

·       Access to the Bookster library and free credits on the Atlas psycho-emotional health platform.

·       An accelerated learning environment, with access to over 100.000 curated online resources and platforms, learning academies and development programs.  

·       A friendly office. We redesigned our headquarter office to suit our hybrid work model: we doubled the number of meeting rooms and we equipped them with state-of-the-art technology.

Curious to find out more about the next step in your career? Apply now and if your experience is relevant for the role you wish, we will give you a call for more details!