Team Leader - Machine Learing

Description

Join a high-energy team delivering large-scale machine learning solutions that power data-driven products. This role combines people leadership with technical oversight, leading Machine Learning Engineers and Data Scientists while driving end-to-end delivery of production-grade machine learning models. Work with engineering, product, and business stakeholders to shape the ML roadmap, ensure technical excellence, and deliver measurable business impact.

Responsibilities

• Lead, mentor, and develop a team of Machine Learning Engineers and Data Scientists, fostering collaboration, ownership, and continuous improvement
• Take responsibility for technical delivery, project milestones, and the overall quality of machine learning solutions
• Plan, coordinate, and oversee end-to-end model-development initiatives from concept through production
• Define and evolve machine learning architecture, feature-engineering strategies, and model-lifecycle standards
• Guide the development, evaluation, calibration, deployment, and continuous improvement of production ML models
• Collaborate with engineering, product, and business stakeholders to align machine learning initiatives with strategic objectives
• Drive cross-functional execution across machine learning, software engineering, and product teams
• Monitor model performance, analyze business impact, and recommend improvements based on experimentation and data insights
• Support adoption of engineering best practices, scalable ML workflows, and modern MLOps standards
• Contribute to long-term technical roadmap planning and the continuous evolution of machine learning capabilities

Requirements

• 8+ years of experience in Machine Learning, Data Science, or related roles delivering production-grade ML solutions
• Minimum 2 years of direct people-management experience leading technical teams
• Proven experience leading end-to-end machine learning projects from data preparation through production deployment
• Strong practical knowledge of the complete ML lifecycle, including feature engineering, model training, evaluation, calibration, deployment, and monitoring
• Advanced programming skills in Python and SQL
• Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow
• Experience with cloud-based ML platforms, preferably Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage)
• Experience building scalable machine learning pipelines and distributed data-processing workflows
• Strong stakeholder-management and communication skills, with experience collaborating across engineering, product, and business teams
• Proven ability to make data-driven decisions based on business metrics and experimentation results
• Experience working with large-scale datasets in production environments
• Native-level Polish
• Good command of English (B2+ level or higher)

Nice to have

• Experience with AdTech, recommendation systems, marketplace platforms, or ranking algorithms
• Experience with MLOps practices, including model artifact repositories, experiment tracking, feature stores, and CI/CD for machine learning
• Experience supporting online inference environments and collaborating with platform engineering teams
• Experience developing click-through rate (pCTR) or conversion prediction (pCVR) models
• Knowledge of distributed data-processing technologies such as Dask or Spark
• Experience leading strategic roadmap planning for machine learning initiatives