About this role
Highlights: Location: Poland, Remote
Stock options
Language: Strong English required (C1)
About Fundraise Up We’re Fundraise Up - a global fundraising platform built to make donating to nonprofits fast, seamless, and accessible to all. Every month, our technology powers tens of millions of dollars in donations across the globe. We focus on innovation that directly impacts results: faster load times, higher conversion rates, global payment support, and accessibility-first design.
Our platform is trusted by many of the world’s leading nonprofits, including UNICEF, the Alzheimer’s Association, and a wide range of global NGOs. With a 4.9/5 rating across top software review platforms, we’re recognized not just for our impact - but for the quality of the product we deliver.
A Truly Global Product We operate in the enterprise segment, serving nonprofit organizations across North America, the United Kingdom, Australia, and Europe.
We’re building a large and complex product ecosystem that serves nonprofits, donors, and partners around the world. The platform includes a modern checkout experience and customizable widgets (each a standalone SPA), donor, organization, and partner portals, admin tools, and several internal apps.
The Team We are a distributed team of 160+ product professionals. Our team members are mainly based across Spain, Poland, Portugal, Georgia, Armenia, Serbia, Turkey, and Cyprus.
Despite our scale, we operate like a focused team - where every task matters and every voice is heard. We value thoughtful collaboration, strong engineering practices, and a product mindset. You’ll be joining a team where quality, mentorship, and mutual respect come first.
About the Role We're looking for an ML Engineer with 5+ years of production experience to own a high-impact client intelligence initiative. Following a successful proof-of-concept with an external consultant, we are bringing this project fully in-house. The ultimate goal is to generate a comprehensive, enriched list of all potential clients globally — understanding their product requirements, industry verticals, and overall revenue potential — and deploy a scoring model that feeds directly into our sales pipeline.
This is an end-to-end ownership role. You will build from the ground up: data collection, enrichment, modeling, and production deployment. The project is co-managed by company executives and has a high strategic value.
What You’ll Do
Build a market intelligence data-base via collecting different types of data (scraping, enrichment), fixing data pipeline and creating an ML model for scoring and analysis of the raw data. Design and operate scrapers to extract key signals from nonprofit websites, including products used, payment tools, and industry vertical indicators. Develop critical filters such as an "Is this website for fundraising?" binary classifier, alongside other features that distinguish high-potential prospects. Source and integrate financial data from international nonprofit registries, as well as third-party signals from SimilarWeb and Facebook. Store and structure the enriched dataset in our internal database, making it accessible and useful across the broader team for research and analysis. Work closely with the sales team to understand their qualification criteria. Analyze disqualified accounts in Salesforce to identify common exclusion patterns and refine scoring accordingly. Deploy the scoring model and own the process of integrating outputs into Salesforce in a clean, maintainable way. Build a scraper to monitor existing clients' websites, tracking whether Fundraise Up tools are correctly implemented across their properties.
Challenges You'll Navigate
At the scale of ~1 million domains, expect domain duplicates, inconsistent data, and significant noise. You'll need to develop robust, cost-efficient filtering pipelines. A single model won't cover everything — you'll likely build several targeted sub-models tailored to specific verticals and geographies as the project matures. All of this needs to be accomplished without incurring high infrastructure or data costs. Pragmatic, scrappy solutions are valued here.
Requirements
5+ years of ML/DS experience solving real product problems Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting) and understanding of modern NLP/LLM approaches Proven experience with large-scale web scraping and data pipeline construction Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV) Strong engineering culture: confident in Python with a product-oriented approach; we value clean code, knowledge of design patterns, and solid engineering practices Advanced SQL; ability to independently build complex datasets in ClickHouse and work with MongoDB MLOps understanding: hands-on experience with experiment tracking and production workflows (Docker, Git, CI/CD) Autonomy: ability to break down ambiguous problems, choose the right tech stack, and deliver to production At Fundraise Up, AI is a default tool, not an experimental one. We expect every team member to actively use AI in their day-to-day work, identify where AI can change the shape of problems in their function, and grow their fluency as the tools evolve. You should already be using AI meaningfully in your work and understand where it adds value and how it can improve the way you operate
Our Tech Stack Core: Python (uv, ruff), FastAPI, Pydantic, Docker
Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)
Data: ClickHouse, MongoDB, pandas, Polars, Redis
MLOps: MLflow, Airflow
Monitoring: Grafana, Sentry
Infra: linux server admin, distributed computation
Bonus points
Curiosity and a hypothesis-driven mindset Ability to communicate complex analytical concepts to non-technical audiences Detail-oriented with a strong sense of ownership Comfort working in fast-paced, data-rich environments
Why work with us
A strong, collaborative product team that owns what it builds Clear product vision and access to real customer feedback from global nonprofit leaders Flat structure: no politics, just great work with great people Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next Long-term focus: we offer equity options and value sustained, meaningful contribution
Benefits
31 days off 100% paid telemedicine plan Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace. English learning courses Relevant professional education Gym or swimming pool Co-working Remote working
**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other characteristic protected by applicable law in the countries where we operate.