Develop and deploy ML solutions using tabular data (uplift models, recommender systems).
Choose ML/LLM approaches or propose alternative solutions.
Build end-to-end ML solutions: data prep, training, API, monitoring.
Design LLM-powered features: classifiers, content generation, chatbots.
LLM lifecycle: datasets, prompt engineering, fine-tuning, evaluation.

🎯 Requirements

5+ years of ML/DS experience solving real product problems.
ML and statistics expertise; gradient boosting; NLP/LLM approaches.
Metrics-driven; tie ML metrics (ROC-AUC, F1, RMSE) to business metrics (CR, LTV).
Strong Python engineering culture; product-focused, clean code, design patterns.
Advanced SQL; build datasets in ClickHouse; work with MongoDB.
MLOps: Docker, Git, CI/CD, production workflows.

🎁 Benefits

31 days off
100% paid telemedicine plan
Home Office Setup Assistance
English learning courses
Co-working
Remote working

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