Machine Learning Team Leader

🌍 Hello World!

We are The Codest - International Tech Software Company with tech hubs in Poland delivering global IT solutions and projects. Our core values lie in “Customers and People First” approach that prioritises the needs of our customers and a collaborative environment for our employees, enabling us to deliver exceptional products and services.

Our expertise centers on web development, cloud engineering, DevOps and quality. After many years of developing our own product - Yieldbird, which was honored as a laureate of the prestigious Top25 Deloitte awards, we arrived at our mission: to help tech companies build impactful product and scale their IT teams through boosting IT delivery performance. Through our extensive experience with product development challenges, we have become experts in building digital products and scaling IT teams.

But our journey does not end here - we want to continue our growth. If you’re goal-driven and looking for new opportunities, join our team! What awaits you is an enriching and collaborative environment that fosters your growth at every step.

Project description:

Our client is one of the largest e-commerce platforms in Europe, used by millions of users every day. The company connects sellers - from small businesses to global brands - with customers, offering a vast product selection, fast delivery, and a well-crafted shopping experience.

The role:

• Ensure that the contractor team delivers high-quality ML Scoring solutions (e.g., click and conversion predictions) for Sponsored Offers on schedule, maintaining responsibility for the team's technical output and project milestones.

• Manage the training scope for deep learning models, including feature space definition and model lifecycle standards.

• Orchestrate the transition of scoring responsibilities from existing teams in cooperation with backend and product stakeholders.

• Provide expert insight to future roadmaps for the ML scope of Sponsored Offers.

Specific skills and tools

• Machine Learning & Analytics: deep learning architectures, model training pipelines, feature engineering, model calibration, A/B testing, offline and online evaluation.

• Platforms & Infrastructure: Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage), workflow orchestration, model artifact lifecycle management.

• Languages & Data: Python, Pytorch/Tensorflow, SQL, distributed data processing concepts (Dask/Spark).

• Leadership: team building, stakeholder communication, roadmap execution, and cross-functional delivery governance.