Fundraise Up

Senior ML-Engineer

Rol remoto de Machine Learning Engineer con fit claro de ubicación del candidato.

Publicado3 jul 2026

Países elegibles41 países aceptados

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

AlbaniaAustriaBielorrusiaBélgicaBulgariaCanadá+35 más

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Las ubicaciones aceptadas para candidatos están listadas (41).

Actualidad de la fuente3 jul 2026

Fit de ubicación41 países aceptados

Match de stackCI/CD, Docker

Camino de aplicaciónSitio de la empresa

Resumen de fit de MiraPor qué vale revisar este rol

Fit de ubicación41 países aceptadosAgrega tu país

Match de stackAgrega skills al perfil para compararCI/CD, Docker

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Preparación para aplicarSitio de la empresaLa aplicación continúa en el sitio de la empresa.

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Aplicación externa

Aplicando aSenior ML-EngineerFundraise Up

Fit de país41 países aceptados

Camino de aplicaciónSitio de la empresa

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Resumen del rol

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Develop and deploy ML solutions across different business areas using tabular data (uplift models, recommender systems). We are also actively developing projects that will involve e-commerce mechanics.
Select the most appropriate ML/LLM approaches or propose alternative solutions.
Build end-to-end ML solutions: data preparation, training, API development, and monitoring.
Design prompts and LLM API-based pipelines for specific product tasks: classification, content generation, and response quality evaluation.

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); NLP knowledge is a plus
Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (CR, LTV)
Strong engineering culture: confident in Python with a product-oriented approach to development; we value clean code, knowledge of design patterns, and solid engineering practices
Data skills: advanced SQL; ability to independently and efficiently build complex datasets in ClickHouse and work with MongoDB
MLOps understanding: hands-on experience with experiment tracking tools and understanding of production workflows (Docker, Git, CI/CD)
Autonomy: ability to break down problems, choose the right tech stack (or justify a non-ML solution), 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

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

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

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