Join Sport Alliance's Data Products team to build and deploy production-ready ML solutions for Magicline and PerfectGym Next. Own models end-to-end, from data pipelines through deployment and monitoring, while collaborating with engineers and product managers. Requires 5+ years of production ML experience, strong Python and SQL skills, and deep expertise in classical ML and statistical methods.
Key Highlights
Build and deploy production-ready ML solutions with a focus on classical ML and statistical methods.
Own models end-to-end, including data preparation, modelling, deployment, and monitoring.
Shape the ML and AI roadmap and identify high-impact opportunities across products.
Work in a small Data Products team alongside data engineers and a data analyst.
Flexible work model: fully remote or on-site in Warsaw.
Key Responsibilities
Build and deploy production-ready ML solutions with a focus on classical ML and statistical methods.
Own models end-to-end, from data pipelines and modelling to deployment and monitoring.
Improve the scalability and reliability of existing ML data pipelines.
Collaborate with software engineers and product managers to turn business problems into practical solutions.
Identify where ML and GenAI can solve real product and business problems, and choose the right approach.
Work with platform and LLM Ops teams when additional infrastructure support is needed.
Help shape the ML and AI roadmap, identifying high-impact opportunities.
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Technical Skills Required
Python
SQL
Machine Learning
Benefits & Perks
Private medical care and sports card
Access to Udemy Business online courses
Flexible work model: fully remote or on-site in Warsaw
Flexible working hours
International, diverse team
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Nice to Have
Experience with AWS, Terraform, or dbt
Experience working with LLMs or GenAI-based solutions
German language skills
Job Description
Join Sport Alliance’s Data Products team and build ML solutions for Magicline and PerfectGym Next, used by thousands of fitness businesses and millions of members.You’ll work closely with engineers and product managers to take ML use cases from idea to production, with plenty of ownership and the opportunity to shape how we use ML and AI across our products.
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