As a Senior Machine Learning Engineer, you will be responsible for the machine learning / data platform in Allegro Pay and support Data Scientists in building machine learning models, making business-critical decisions, and enabling shipping models to production while ensuring their high availability and performance.
Technologies you’ll encounter on the job are (among others) Python, Snowflake, Airflow, Azure, Kedro, MLFlow, .NET, Kubernetes, Tableau
responsibilities :
Develop a modern MLOps ecosystem aimed at automating the process of building and deploying machine learning models,
Extend platform capabilities in GenAI space,
Design and implement a modern platform for training predictive models (classifiers & regression, deep neural networks, graph models),
Deploy models to production and optimise deployment pipelines, to enable Data Scientists’ self-service,
Manage, monitor, and recalibrate models deployed to production,
Support work on our Feature Store - an application providing predictors for models operating in production,
Work with diverse data structures, such as geographic data, event sequences, digital device fingerprints,
Align ML platform roadmap with business and research needs through collaboration with diverse stakeholders,
Support and advise junior ML Engineers in your space.
requirements-expected :
Our offer is addressed to people who:
Graduated with a degree in Computer Science, Mathematics or another technical major
Have at least 3 years of experience in building ML-driven solutions
Fluently program in Python, know libraries from the MLE’s toolchain (scikit-learn, PyTorch/tensorflow, Pandas, FastAPI/Flask) and use development tools with ease
Has experience with modern Python-based orchestration tools (Airflow, Dagster)
Has worked with MLOps tooling like Azure ML, AWS Sagemaker, Kubeflow, MLFlow
Has good analytical skills and know SQL
Knows and applies the DevOps principles in their work
Understand statistical and machine learning methods, especially algorithms based on decision trees and neural networks, on a practical level
Are able to make independent decisions within the scope of their responsibilities and take ownership of the code they created
offered :
Community of experienced Machine Learning/Data/Software Engineers & Data Scientists - there is always someone to exchange ideas with because we have the best specialists and experts in their field on board
Possibility to lead implementation ML solutions which are unique on the market
Our office, which is located in one of the most vibrant and desirable locations in Warsaw - Fabryka Norblina. We enjoy numerous lunch spots, fully equipped kitchens, bicycle parking facilities and excellent working tools (height-adjustable desks, interactive conference rooms)
A wide selection of fringe benefits in a cafeteria plan – you choose what you like (e.g. medical, sports or lunch packages, insurance, purchase vouchers)
Annual bonus of up to 10% of the gross annual salary (depending on your end-year assessment and the companys results)
Long-term discretionary incentive plan based on Allegro.eu shares
Fully sponsored English classes, related to the specific nature of your job
benefits :
sharing the costs of sports activities
private medical care
sharing the costs of foreign language classes
sharing the costs of professional training & courses
