Machine Learning Research Team Leader

Our requirements

• 8+ years of commercial experience in Machine Learning or Data Science in production environments.
• At least 2 years of proven people management experience (mandatory).
• Strong experience leading end-to-end model training initiatives for business-critical use cases.
• Hands-on expertise across the full ML lifecycle, including data preparation, feature engineering, model training, evaluation, calibration and production rollout.
• Advanced knowledge of Python, SQL and deep learning frameworks such as PyTorch or TensorFlow.
• Experience working with Google Cloud Platform, particularly Vertex AI, BigQuery and Cloud Storage, as well as scalable data processing concepts (e.g. Dask or Spark).
• Strong understanding of ML infrastructure, including model lifecycle management, workflow orchestration, A/B testing and offline/online model evaluation.
• Ability to lead cross-functional initiatives and communicate effectively with technical teams and Director-level stakeholders.
• Strong business mindset with experience making data-driven decisions based on metrics such as revenue, GMV and conversion.
• English level B2+.

Optional

• Experience in AdTech, recommendation systems or marketplace ranking.
• Experience building pCTR, pCVR or similar prediction models.
• Familiarity with CI/CD for Machine Learning, experiment tracking frameworks, feature stores and model artifact repositories.
• Experience working with online inference platforms and production ML serving environments.

Your responsibilities

• Lead, mentor and develop a team of Machine Learning Engineers and Data Scientists, ensuring high-quality delivery and team growth.
• Oversee the end-to-end development of ML scoring models supporting Sponsored Offers, including click and conversion prediction.
• Drive model training initiatives covering feature engineering, model calibration, offline and online evaluation, controlled rollouts and experimentation.
• Manage the transition of ML scoring responsibilities across teams and coordinate delivery with Product, Engineering and Platform stakeholders.
• Define technical standards for model lifecycle management, workflow orchestration and scalable ML development.
• Provide strategic input into the ML roadmap and communicate progress, risks and business impact to senior stakeholders.
• Foster cross-functional collaboration and ensure projects are delivered on time and aligned with business objectives.

About the project

What we offer

• We focus on long-term relationships based on fair principles and reliability.
• Co-financing of the Multisport card and Medicover private healthcare.
• Modern office available.
• Team bonding activities, internal courses, conferences, certifications.

Benefits

• sharing the costs of professional training & courses
• flexible working time
• integration events
• video games at work
• parking space for employees
• leisure zone

PRETIUS SOFTWARE SP. Z O.O.