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, including uplift models and recommender systems.
  • Select appropriate ML and LLM approaches, or propose alternative solutions when they are a better fit.
  • Build end-to-end ML systems covering data preparation, training, API development, and monitoring.
  • Design LLM-powered features such as classifiers, content generation tools, AI assistants, and chatbots.
  • Own the full LLM lifecycle, including golden datasets, prompt engineering, fine-tuning, and response evaluation.
  • Work on projects related to donation optimization, upsell offers, admin panel assistants, transaction classification, and e-commerce mechanics.
  • Collaborate with internal product teams as an ML center of excellence serving 10+ product teams.
  • Deliver solutions to production with an emphasis on performance, reliability, and business impact.

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 engineering skills with a product-oriented mindset, clean code habits, design patterns, and solid engineering practices.
  • Advanced SQL skills and the ability to independently build complex datasets in ClickHouse.
  • Experience working with MongoDB.
  • Hands-on experience with experiment tracking tools and understanding of production workflows such as Docker, Git, and CI/CD.
  • Ability to break down problems, choose the right tech stack, and justify non-ML solutions when appropriate.
  • English at B2 level or higher; Russian-speaking team environment.
  • Experience with LLMs, RAG, prompt engineering, or fine-tuning is a plus.
  • Familiarity with the company tech stack, including FastAPI, Pydantic, CatBoost, CausalML, MLflow, Airflow, Grafana, and Sentry, is preferred.

Benefits

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

Interested in this position?

Apply directly on the company website

Apply Now

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