Software Engineer (Java/Python + Machine Learning)

Project overview

Hi! Discover the possibilities of collaborating with Scalo!

At Scalo, we focus on delivering software projects and supporting our partners in growing their businesses. We create software that empowers people to make changes, act faster, and achieve better results. We utilize a wide spectrum of IT services to support our clients in achieving their business goals.

Our areas of activity include, among others:

What do we offer as part of the collaboration?

• technology consulting,
• software creation,
• embedded systems,
• cloud solutions,
• data management,
• dedicated project teams.
• the opportunity to provide services in various projects within Software, Embedded, Data, and Cloud Services,
• involvement in additional pre-sales and expert initiatives,
• access to medical care, a sports card, and a cafeteria platform according to current cooperation rules.
• participation in an e-commerce industry project,
• designing, developing, and maintaining applications and backend solutions in Java, using Python for data processing and Machine Learning model development,
• creating high-quality, readable, and efficient code ready for deployment to production environments,
• developing and deploying predictive models based on supervised learning, used in business solutions for the e-commerce industry,
• preparing, processing, and analyzing large tabular datasets using Pandas and NumPy libraries,
• building, training, and optimizing regression models, particularly using Gradient Boosting algorithms (e.g., LightGBM) and scikit-learn,
• designing and implementing the Feature Engineering process, including preparing features for predictive models and time series data,
• designing and conducting model validation, considering the specifics of time series data, selecting appropriate metrics, and evaluating prediction quality and stability,
• comparing model results with baseline solutions and identifying and eliminating problems related to overfitting, data leakage, and data processing inconsistencies between training and production environments,
• integrating Machine Learning models with Java-based backend applications and ensuring their proper functioning in the production environment,
• collaborating on the design and development of architectures for solutions that enable efficient sharing and utilization of ML models by business applications,
• participating in code reviews, testing, performance optimization, and maintenance of developed solutions,
• collaborating with an international project team, data analysts, and other technical specialists to deliver solutions that meet business needs.
• minimum 4 years of commercial experience in a similar role,
• very good knowledge of Java,
• practical knowledge of Python,
• experience in creating clean, readable, and efficient code ready for deployment to production environments,
• good knowledge of Machine Learning concepts, especially Supervised Learning,
• practical experience in building predictive models on tabular data, particularly regression models,
• knowledge of Gradient Boosting algorithms and practical experience with the LightGBM library,
• experience in preparing, processing, and analyzing large datasets using Pandas and NumPy libraries,
• practical knowledge of scikit-learn and/or LightGBM libraries for building, training, and evaluating Machine Learning models,
• knowledge of Feature Engineering concepts, including preparing features for predictive models,
• ability to design model validation considering time series data characteristics and selecting appropriate evaluation metrics,
• ability to compare model results with a baseline model and identify problems such as overfitting and data leakage,
• awareness of the importance of data processing and feature calculation consistency between training and production environments,
• ability to integrate Machine Learning models with Java-based applications,
• knowledge of English at C1 level, enabling fluent communication in an international project environment.

Nice to have

• practical knowledge of Quantile Regression,
• experience in Feature Engineering for Time Series data,
• knowledge of SQL,
• experience with AWS services, particularly S3 and Athena,
• knowledge of Docker and Kubernetes,
• experience with CI/CD processes,
• knowledge of monitoring tools, particularly Prometheus,
• experience with Machine Learning solutions used in production environments.

Project details

• Start: ASAP
• Remote: hybrid
• Location: Remote, Kraków, PL
• Rate: 115-125 EUR/h
• Languages: English, Polish