About 

Combining the world of entertainment and data science can be something truly special: where else could you influence what gets broadcast on the most-watched TV station or what new content appears on Oneplay? We are the largest commercial TV network in Central Europe and video platform with largest number of subscribers in Czechia. We are now looking for someone to expand our AI/ML team and help us take AI in the company to the next level. 

The Mission: 

You will be a key player in our content personalization. Your mission is to help connect our viewers with the exact content they want to watch by developing and maintaining Recommender Systems using Deep Learning architectures. 

What will you do? 

• Build, train, and deploy machine and deep learning models to power our Recommender Systems. 
• Collaborate on the Deep Learning lifecycle: working with the team to move from a theoretical task to a working PoC, and helping scale it to a production-ready solution. 
• Help deliver recommendations as APIs for our vendors or as enriched tables in our Data Warehouse (DWH). 
• Write clean, tested code, participate in peer code reviews, and follow our CI/CD best practices. 
• Keep up with RecSys research and assist in experimenting with new architectures. 

What do we require? 

• Solid proficiency in Python and PyTorch. 
• Practical experience or strong academic background in Deep Learning architectures (e.g., sequence modeling, embeddings). Experience with Recommender Systems is a plus.
• Familiarity with SQL. Any exposure to cloud platforms (Azure/AWS) or data processing tools (PySpark, Databricks) is a nice-to-have.
• A curious problem-solver. Enjoy experimenting and prototyping, but understand value of clean code.
• Basic understanding of Docker or containerization is a bonus. 

Why work in our ML team: 

• We do truly innovative things in the online and linear media world (RecSys, causal inference, GenAI). 
• We run projects with real business impact. 
• Your opinion matters – you'll be part of the full development cycle. 
• We enjoy what we do because our work is meaningful. 

What we offer: 

• Praticipation on AI/ML conferences (paid by a company),  
• A pleasant work environment, a down-to-earth team, and good coffee. 
• A hybrid work model. 
• 5 weeks of vacation and 8 additional days off per year. 
• Competitive salary and a generous benefits package.