Machine Learning Research Team Leader

At Pretius we are looking for a Machine Learning Research Team Leader to a large-scale e-commerce platform development.

• 8+ years of commercial experience in Machine Learning or Data Science in production.
• At least 2 years of proven people management experience.
• Strong experience leading end-to-end model training for business-critical cases.
• Hands-on expertise in the full ML lifecycle: data preparation, feature engineering, model training, evaluation, calibration, and rollout.
• Advanced knowledge of Python, SQL, and deep learning frameworks such as PyTorch or TensorFlow.
• Experience working with Google Cloud Platform, especially Vertex AI, BigQuery, and Cloud Storage.
• Knowledge of scalable data processing concepts like Dask or Spark.
• Understanding of ML infrastructure including lifecycle management, workflow orchestration, A/B testing, and evaluation.
• Ability to lead cross-functional initiatives and communicate with technical and Director-level stakeholders.
• Strong business mindset with data-driven decision experience based on revenue, GMV, and conversion metrics.
• English language proficiency at B2+ level.

Nice to have:

• 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, feature stores, and model artifact repositories.
• Experience with online inference platforms and production ML serving environments.

• Lead, mentor and develop a team of Machine Learning Engineers and Data Scientists.
• Oversee the end-to-end development of ML scoring models for Sponsored Offers.
• Drive model training initiatives including feature engineering, calibration, evaluation, rollouts, and experimentation.
• Manage transition of ML scoring responsibilities across teams and coordinate deliveries with stakeholders.
• Define technical standards for model lifecycle management, workflow orchestration, and scalable ML development.
• Provide strategic input into the ML roadmap and communicate progress and risks to senior stakeholders.
• Foster cross-functional collaboration to ensure projects meet business objectives and timelines.