Fundraise Up

Fundraise Up

Fundraise Up specializes in enhancing online donation processes through AI-driven conversion optimization and integrated payment solutions, enabling organizations to maximize their fundraising potential and improve donor engagement.

Capital Markets
51-250
Founded 2017

Description

  • Develop and deploy ML solutions across multiple business areas using tabular data, uplift models, and recommender systems.
  • Select appropriate ML or LLM approaches, or propose non-ML alternatives when they are more effective.
  • Build end-to-end ML solutions covering data preparation, training, API development, and monitoring.
  • Design LLM-powered features such as classifiers, content generation tools, AI assistants, and chatbots.
  • Work across the full LLM lifecycle, including golden datasets, prompt engineering, fine-tuning, and response evaluation.
  • Collaborate with internal product teams as an internal ML service and center of excellence.
  • Apply metrics-driven decision-making by connecting model metrics to business outcomes.
  • Deliver production-ready solutions with strong engineering and MLOps practices.

Requirements

  • 5+ years of ML or data science experience solving real product problems.
  • Strong expertise in machine learning and mathematical statistics, including classical algorithms such as gradient boosting.
  • Understanding of modern NLP and LLM approaches.
  • Ability to connect ML metrics such as ROC-AUC, F1, and RMSE with business metrics such as CR and LTV.
  • Strong Python skills with a product-oriented approach, clean code habits, design patterns, and solid engineering practices.
  • Advanced SQL skills and experience building complex datasets in ClickHouse.
  • Experience working with MongoDB.
  • Hands-on experience with experiment tracking tools and production workflows such as Docker, Git, and CI/CD.
  • Ability to break down problems, choose the right tech stack, or justify a non-ML solution and deliver to production.
  • Strong English required at B2 level; the team primarily communicates in Russian.
  • Experience with e-commerce mechanics, RL, or broader LLM solutions is a plus.
  • Experience with MLflow and Airflow is a plus.

Benefits

  • 31 days off.
  • 100% paid telemedicine plan.
  • Home office setup assistance, including support for furniture and equipment purchases.
  • English learning courses.
  • Relevant professional education support.
  • Gym or swimming pool access.
  • Co-working support.
  • Remote working from Poland.

Interested in this position?

Apply directly on the company website

Apply Now

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