Highlights

• OTE: USD$122k-132k
• Location: remote in North America (EST and CST)
• Stock options

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.

About The Role

Overview

This is a foundational hire and a rare opportunity to build a critical function from the ground up. As the first dedicated Payroll & Equity Lead, you will establish how payroll and equity operate across a truly global, distributed workforce—spanning multiple countries, entities, and employer-of-record partners. You will not be stepping into a pre-built system; you will define it.

The role is designed for someone who is comfortable operating at a multi-country level, navigating complexity across jurisdictions, and bringing structure to an environment that is scaling quickly. You will set the standards, controls, and processes that ensure payroll and equity are accurate, compliant, and audit-ready as the company grows. This is a high-impact position with direct visibility across Finance, People, Legal, and Revenue Operations, where your work will shape how the company manages two of its most sensitive and high-trust operations.

Key Responsibilities

• Own end-to-end payroll delivery for all non-GTM employees globally, ensuring accuracy, timeliness, and consistency across multiple jurisdictions, entities, and EOR partners
• Establish and manage a standardized payroll calendar, including clear cutoffs, review cycles, funding timelines, and disbursement schedules
• Partner with Revenue Operations to incorporate finalized GTM payroll inputs and execute payments within a unified, controlled framework
• Ensure compliance with local payroll regulations, tax requirements, and statutory obligations across all countries of operation, coordinating with external providers and advisors
• Manage relationships with EOR partners, including funding requests, reconciliations, issue resolution, and establishing a forward-looking funding cadence aligned with Finance and Treasury
• Administer equity programs end-to-end, including new grants, exercises, and terminations, while maintaining cap table accuracy and integrity
• Partner with Finance and Legal on equity-related processes, including 409A valuations and ensuring alignment with ASC 718 reporting requirements
• Design and implement a scalable payroll and equity controls framework, including independent review, general ledger reconciliation, variance analysis, and audit-ready documentation
• Serve as the primary point of contact for internal and external audits related to payroll and equity
• Act as a trusted internal partner, supporting employee questions on payroll and equity, and collaborating with People Ops on onboarding, offboarding, and compensation changes
• 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.

Skills and Qualifications

Required

• 5+ years of multi-country payroll experience, including direct entities and EOR models
• Hands-on experience with an equity administration platform (e.g., Carta, Shareworks, Pulley)
• Working knowledge of stock-based compensation accounting (ASC 718)
• Demonstrated experience building or improving payroll controls in a scaling environment
• Ability to operate independently and establish structure in an ambiguous environment
• Strong cross-functional collaboration skills (Finance, People Ops, Revenue Operations, Legal)
• High attention to detail, discretion, and ability to manage deadlines in a close cycle

Preferred

• CPP (Certified Payroll Professional) or equivalent certification
• Experience in a high-growth or venture-backed company
• Experience managing EOR vendors (e.g., Deel, Remote, Velocity Global)
• Familiarity with global equity tax treatment (ISO, NSO, RSU, ESPP and international equivalents)

Perks & Benefits

• Health, Dental, and Vision insurance covered at 100% for employees, 80% for employee plus dependents, and 70% for employees plus family.
• FSA and HSA Spending Account.
• 20 days of vacation, 5 sick days, 11 company holidays plus an additional 1 floating holiday.
• 401(k) plan with company match.
• 100% Company-paid short-term disability, long-term disability, basic life insurance and AD&D.
• Paid parental leave (12 weeks for primary caregivers / 6 weeks for secondary caregivers).
• Generous home office stipend to support your remote workspace.
• Annual professional development stipend to support your growth (e.g., workshops, courses, and seminars).
• Charitable giving program and paid volunteer time off with registered non-profits.

_{**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.***}

Highlights

• OTE: GBP £64k-70k
• Location: remote in the UK
• Stock options

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.

About The Role

This is a foundational hire and a rare opportunity to build a critical function from the ground up. As the first dedicated Payroll & Equity Lead, you will establish how payroll and equity operate across a truly global, distributed workforce—spanning multiple countries, entities, and employer-of-record partners. You will not be stepping into a pre-built system; you will define it.

The role is designed for someone who is comfortable operating at a multi-country level, navigating complexity across jurisdictions, and bringing structure to an environment that is scaling quickly. You will set the standards, controls, and processes that ensure payroll and equity are accurate, compliant, and audit-ready as the company grows. This is a high-impact position with direct visibility across Finance, People, Legal, and Revenue Operations, where your work will shape how the company manages two of its most sensitive and high-trust operations.

Key Responsibilities

• Own end-to-end payroll delivery for all non-GTM employees globally, ensuring accuracy, timeliness, and consistency across multiple jurisdictions, entities, and EOR partners
• Establish and manage a standardized payroll calendar, including clear cutoffs, review cycles, funding timelines, and disbursement schedules
• Partner with Revenue Operations to incorporate finalized GTM payroll inputs and execute payments within a unified, controlled framework
• Ensure compliance with local payroll regulations, tax requirements, and statutory obligations across all countries of operation, coordinating with external providers and advisors
• Manage relationships with EOR partners, including funding requests, reconciliations, issue resolution, and establishing a forward-looking funding cadence aligned with Finance and Treasury
• Administer equity programs end-to-end, including new grants, exercises, and terminations, while maintaining cap table accuracy and integrity
• Partner with Finance and Legal on equity-related processes, including 409A valuations and ensuring alignment with ASC 718 reporting requirements
• Design and implement a scalable payroll and equity controls framework, including independent review, general ledger reconciliation, variance analysis, and audit-ready documentation
• Serve as the primary point of contact for internal and external audits related to payroll and equity
• Act as a trusted internal partner, supporting employee questions on payroll and equity, and collaborating with People Ops on onboarding, offboarding, and compensation changes
• 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.

Skills and Qualifications

Required

• 5+ years of multi-country payroll experience, including direct entities and EOR models
• Hands-on experience with an equity administration platform (e.g., Carta, Shareworks, Pulley)
• Working knowledge of stock-based compensation accounting (ASC 718)
• Demonstrated experience building or improving payroll controls in a scaling environment
• Ability to operate independently and establish structure in an ambiguous environment
• Strong cross-functional collaboration skills (Finance, People Ops, Revenue Operations, Legal)
• High attention to detail, discretion, and ability to manage deadlines in a close cycle

Preferred

• CPP (Certified Payroll Professional) or equivalent certification
• Experience in a high-growth or venture-backed company
• Experience managing EOR vendors (e.g., Deel, Remote, Velocity Global)
• Familiarity with global equity tax treatment (ISO, NSO, RSU, ESPP and international equivalents)

Perks & Benefits

• Health, Dental, and Vision insurance covered at 100% for employees, 80% for employee plus dependents, and 70% for employees plus family.
• FSA and HSA Spending Account.
• 20 days of vacation, 5 sick days, 11 company holidays plus an additional 1 floating holiday.
• 401(k) plan with company match.
• 100% Company-paid short-term disability, long-term disability, basic life insurance and AD&D.
• Paid parental leave (12 weeks for primary caregivers / 6 weeks for secondary caregivers).
• Generous home office stipend to support your remote workspace.
• Annual professional development stipend to support your growth (e.g., workshops, courses, and seminars).
• Charitable giving program and paid volunteer time off with registered non-profits.

_{**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.***}

Highlights:

• OTE (On-Target Earnings): $173,250 - $187,000
• Location: US Remote (EST, CST)
• Reports to: Director, Business Operations (Finance)

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.

About The Role

The Lead AI Engineer is a highly technical role dedicated to building and deploying production-level AI solutions at Fundraise Up. Partnering closely with the AI Product Lead, you will take strategic blueprints and turn them into scalable, robust technical realities. This role demands deep expertise in modern AI frameworks, from RAG-based systems to complex agentic architectures, ensuring that our technical deployments are secure, efficient, and deeply integrated into our operational workflows.

What You'll Do

• Agent Architecture Design: Define precise technical requirements for scalable agent architecture, including necessary reasoning frameworks, risk management systems, and knowledge retrieval interfaces required for complex decision-making.
• End-to-End Build Capability: Serve as the hands-on technical lead capable of building, testing, and deploying both interim (e.g., RAG-based systems) and highly complex agentic AI solutions.
• Technical Implementation: Work alongside strategy leads to ensure that the technical prerequisites for achieving fully autonomous agentic operations are met on the twelve-month roadmap.
• Operational Scaling & Integration: Oversee the technical integration and scaling of deployed AI agents within specific operational workflows (e.g., automating specific GTM tasks).
• Validation & Testing: Ensure seamless deployment with rigorous validation testing, monitoring agent performance, and iterating on technical builds to improve decision accuracy and reduce latency.
• 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.

About You

• 5+ years in software engineering, AI engineering, or technical architecture within high-growth technology environments or AI startups.
• Proven hands-on experience in the technical build and deployment of LLM-powered applications, RAG systems, and agentic workflows.
• Deep understanding of the modern AI tech stack, prompt engineering, API integrations, and scalable deployment infrastructure.
• Proven ability to execute complex technical work streams with limited oversight and high accountability.
• Strong technical communicator; able to explain complex architectural decisions and technical trade-offs to non-technical strategic partners.
• A practical, shipping-oriented approach — you are motivated by building reliable, production-ready systems that solve real business problems.

Perks & Benefits

Our compensation package includes comprehensive benefits and perks, meaningful equity, and a competitive salary:

• Health, Dental, and Vision insurance covered at 100% for employees, 80% for employee plus dependents, and 70% for employees plus family.
• FSA and HSA Spending Account.
• 20 days of vacation, 5 sick days, 11 company holidays plus an additional 1 floating holiday.
• 401(k) plan with company match.
• 100% Company-paid short-term disability, long-term disability, basic life insurance and AD&D.
• Paid parental leave (12 weeks for primary caregivers / 6 weeks for secondary caregivers).
• Generous home office stipend to support your remote workspace.
• Annual professional development stipend to support your growth (e.g., workshops, courses, and seminars).
• Charitable giving program and paid volunteer time off with registered non-profits.

Highlights:

Role: Senior ML-Engineer, Finance

Location: Cyprus, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Georgia, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Portugal, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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

• 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.
• Gym or swimming pool.
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• Co-working.
• Remote working.
• €50 monthly allowance to cover internet and mobile phone expenses

_{**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.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Serbia, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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

• Private medical insurance for the employee and their family
• 20 paid vacation days per year
• 15 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• 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.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Spain, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• 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.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Turkey, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Armenia, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Poland, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

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

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.}