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.}

At JetBrains, code is our passion. Ever since we started, back in 2000, we have been striving to make the most effective developer tools on earth. Our tools speed up production by automating routine checks and corrections, freeing developers to grow, discover, and create.

The Business Applications Development team is a vital integrational hub within JetBrains. We are focused on supporting businesses by automating sales flow and license management, as well as by developing other internal and external services. We ensure the completeness, continuity, and high quality of JetBrains’ sales and licensing processes. Our solutions are a family of web applications written mostly in Kotlin.

We are currently looking for a Senior QA Engineer to join the team and support our efforts.

As part of our team, you will: 

• Design, improve, and execute test scenarios for new and existing functionalities.
• Use an exploratory testing approach on a daily basis.
• Investigate, identify, and reproduce complex issues reported by users.
• Participate in discussions about new projects and review feature requirements.
• Communicate closely with your teammates and other teams to find optimal solutions.

We’ll be happy to have you on our team if you: 

• Have at least 3 years (preferred) of experience in web applications or SaaS testing (white box).
• Have good knowledge of browser tools such as DevTools, Postman, and various code sniffers.
• Can read and write code in Java/Kotlin.
• Are comfortable writing complex SQL queries to get the data you need.
• Strive to clearly understand the architecture of the applications you test.
• Understand web application security mechanisms.
• Are capable of working with different processes and in varied environments.
• Are open to other points of view and can reasonably defend your own.
• Adhere to the principle that decisions should be based on facts.

We’ll be especially thrilled if you: 

• Have a basic understanding of containerization principles.
• Can easily use *nix command tools like man, grep, find, sed, netstat, and awk

#LI-DNI

We're building an AI copilot for web testing automation. It enables manual and automation QA engineers to turn their manual testing flows into production-ready automated E2E testing scripts, saving hours of manual work and coding. We are a small team with zero bureaucracy, focusing on real users. We optimize for shipping value - not hype.

About the role:

You'll own the top of the funnel: outbound, qualification, and getting leads to sit down for a conversation. Demos, onboarding, and retention are staying with the founder for now.

Phase one: Get individual Automation QAs to try the product, aiming for fast adoption and no procurement. Once we hit 20+ weekly users, we’ll move on to phase two, where we’ll shift the focus to B2B – qualified meetings with QA Leads and Engineering Managers.

Your focus in the first three months:

• Build targeted lists: Automation QAs at companies with web products and Playwright, Cypress, or Selenium in their stack.
• Run outbound sequences (LinkedIn is the baseline, but you decide the channels). A/B test weekly.
• Design qualification gates (forms and scoring) to filter leads before the founder calls.
• Reach 20+ weekly active users after month one – ICP-qualified and giving direct feedback to engineering.
• Document what works into a repeatable playbook.

Growth path:

This role expands as your strategies deliver results. Once the user pipeline works, you can take over demos and run B2B sales end to end. From there, the natural next step is Growth Lead (funnel optimization and scaling the playbook) or Account Executive (owning deal execution).

Why to join:

• You'll be building a strategy that scales the product, not filling a quota. What you create from scratch becomes the foundation.
• Your outreach turns into users who talk directly to engineering, and their feedback ships as features within days.
• AI for developer tools is a market with real pull, and QA automation is one of its sharpest pain points.
• We’re backed by JetBrains – financially secure with no reliance on external VC funding.

Who we're looking for:

You should have a high level of agency and be quant-minded – you live in funnel metrics, run experiments, and are comfortable saying "no" to leads that are a bad fit. 

The ideal candidate will:

• Have done 0-to-1 outbound for an early-stage devtool, QA tool, infrastructure product, or similar.
• Have proven cold outbound results, instead of being dependent on warm inbound.
• Be able to talk credibly about flaky tests, CI pain, and Playwright vs. Cypress. You don't need to be an engineer, but you do need domain empathy.
• Possess strong written communication skills, with the ability to craft short, sharp messages that get replies.

Nice to have:

• A QA or SDET background – you've felt the pain yourself before moving to sales or BD.
• Exposure to security/compliance objections – enough to pre-empt and route.
• Content skills – your LinkedIn posts get engagement, not just your DMs.
• Experience as one of the first 10 employees at a startup.

#LI-REMOTE 
#LI-KT1