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 the most appropriate ML, LLM, or alternative approaches for each problem.
  • Build end-to-end ML solutions, 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 on use cases such as optimizing donation amounts, upsell offers, smart assistants, and transaction classification.
  • Collaborate with internal product teams as a centre of excellence for ML support across the company.

Requirements

  • 5+ years of ML/DS experience solving real product problems.
  • Strong knowledge of classical ML algorithms, especially gradient boosting, and understanding of modern NLP/LLM approaches.
  • Solid grounding in mathematical statistics and a metrics-driven mindset that connects ML metrics to business outcomes.
  • Strong Python engineering skills with a product-oriented approach, clean code, design patterns, and solid engineering practices.
  • Advanced SQL skills and experience building complex datasets in ClickHouse and working with MongoDB.
  • Hands-on experience with MLOps tools and production workflows, including experiment tracking, Docker, Git, and CI/CD.
  • Ability to break down problems independently, choose the right tech stack, or justify a non-ML solution and deliver to production.
  • Strong English required at B2 level.
  • Experience with classical ML, RL, and LLM-based solutions is preferred.
  • Familiarity with the existing stack, including FastAPI, Pydantic, MLflow, Airflow, Grafana, and Sentry, is a plus.

Benefits

  • Private medical insurance for the employee and their family.
  • 22 paid vacation days per year.
  • Up to 14 paid public holidays per year.
  • 5 company-paid sick leave days.
  • English learning courses.
  • Relevant professional education support.
  • Gym or swimming pool access.
  • Home office setup assistance, including furniture and equipment support.
  • Co-working support and remote working options.
  • €50 monthly allowance for internet and mobile phone expenses.
  • Equity options for long-term contribution.

Interested in this position?

Apply directly on the company website

Apply Now

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