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 different business areas, including tabular-data use cases such as uplift modeling and recommender systems.
  • Select appropriate ML or LLM approaches, or propose alternative solutions when they are more effective.
  • Build end-to-end ML systems, including data preparation, model 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 across an internal ML service that supports 10+ product teams and contributes to multiple product areas.
  • Optimize business outcomes such as donation amounts, upsell offers, admin-panel assistance, and transaction classification.

Requirements

  • 5+ years of ML or data science experience solving real product problems.
  • Strong knowledge of classical machine learning and mathematical statistics, especially gradient boosting.
  • Understanding of modern NLP and LLM approaches, including generation, classification, and agents.
  • Metrics-driven mindset with ability to connect ML metrics such as ROC-AUC, F1, and RMSE to business metrics such as CR and LTV.
  • Strong Python development skills with a product-oriented approach, clean code, design patterns, and solid engineering practices.
  • Advanced SQL skills and ability to build complex datasets in ClickHouse independently; experience with MongoDB.
  • Hands-on MLOps 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, and deliver solutions to production independently.
  • Strong English required at B2 level; the team primarily communicates in Russian.
  • Experience with RL is a plus.
  • Experience with e-commerce mechanics is a plus.
  • Familiarity with tools in the current stack such as FastAPI, Pydantic, CatBoost, CausalML, OpenAI, MLflow, Airflow, Grafana, Sentry, pandas, Polars, and Redis is a plus.

Benefits

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

Interested in this position?

Apply directly on the company website

Apply Now

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