Machine Learning Engineer

About the project

The client is building a B2B marketplace for surplus inventory that helps businesses reduce waste and improve supply-chain efficiency. The product operates at the intersection of pricing, supply, and demand, and market intelligence, where Machine Learning is a core competitive advantage. This is an early-stage product with no legacy code, a modern tech stack, and close collaboration with the founders. Machine Learning here is not a supporting function but a foundation of the platform’s business logic and growth.

Your area of responsibility

• Designing and building the ML and data architecture from scratch, aligned with business goals;
• Developing pricing, demand forecasting, and optimization models for a B2B marketplace;
• Translating supply-and-demand challenges into scalable ML solutions;
• Defining data collection, feature engineering, and model evaluation approaches;
• Deploying, monitoring, and iterating on models in a production environment;

• Collaborating closely with founders to shape the ML roadmap and long-term strategy.

   

Skills and requirements

• 5+ years of experience in Machine Learning and/or Software Engineering, with a proven track record of delivering ML solutions to production;
• Strong Python skills and hands-on experience with classical ML frameworks (scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow);
• Solid understanding of pricing-related domains: regression models, time-series forecasting, econometrics, or optimization techniques;
• Experience designing end-to-end ML pipelines, from data collection and feature engineering to deployment and monitoring;
• Strong SQL skills and experience working with cloud-based data platforms (PostgreSQL / Supabase is a plus);
• Ability to work independently in ambiguous, early-stage environments and translate business goals into technical solutions.

Will be a plus

• Previous experience in B2B marketplaces, e-commerce pricing, or fintech products;
• Ability to work beyond ML tasks, including tweaking backend APIs or writing SQL functions to retrieve and prepare data;
• Hands-on experience with MLOps tools and practices, such as Docker, Airflow, or specialized frameworks like ZenML or BentoML.

We offer

• Working in a team of talented and passionate engineers;
• Opportunity to work with the most trending technologies;
• Long-term enjoyable cooperation;
• Personal legal support;
• English classes;
• Paid vacation and sick days;
• Competitive salary depending on your own talents;
• Regular performance & career development reviews;
• Team building events.