Machine Learning Engineer

TL;DR

Machine Learning Engineer (PyTorch/TensorFlow): Analyze large-scale marketing and product datasets, build, test, and improve machine learning models with an accent on data preprocessing, feature engineering, and validation. Focus on developing data-driven hypotheses, supporting business decision-making, and projects in marketing performance and creative analysis including video and computer vision tasks.

On-site / hybrid work format in our Prague office

Company

Digital marketing and advertising technology ecosystem partnering with TikTok, Meta, and Google to drive performance and help brands scale worldwide.

What you will do

• Analyze large-scale marketing and product datasets
• Build, test, and improve machine learning models
• Perform data preprocessing, feature engineering, and validation
• Develop data-driven hypotheses and support business decision-making
• Work on projects related to marketing performance and creative analysis
• Collaborate with analytics, product, and engineering teams

Requirements

• 3+ years of experience in Machine Learning, Data Science, or similar roles
• Strong Python skills
• Experience with at least one of: PyTorch, TensorFlow, or scikit-learn
• Solid understanding of machine learning fundamentals, statistics, and data analysis
• Experience working with real-world datasets
• Good SQL skills
• English level B1+ (ability to read technical documentation and research materials)

Nice to have

• Experience working with marketing or advertising data
• Experience with video or image data, including computer vision tasks
• Experience with LLM or GenAI-related tasks
• Participation in Kaggle or similar competitions
• Basic understanding of MLOps or model deployment
• Experience with cloud platforms such as AWS, GCP, or Azure

Culture & Benefits

• Flexible working hours: start between 9:00–11:00 CET
• All necessary equipment provided
• Paid vacation and sick leave
• Company events and internal activities
• Open feedback and transparent communication
• Dynamic culture driven by speed, analytics, and results