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

Financials

51-250 (100)

Founded 2017

82 open positions

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Senior ML-Engineer

1 month, 4 weeks ago

Portugal

Full-time

Senior

Machine Learning Engineer

Software Development

Apache Airflow CatBoost CI/CD ClickHouse Docker FastAPI Git Grafana LLM Machine Learning MLflow MongoDB NLP Pandas Python Redis Reinforcement Learning SQL

Apply Now

Fundraise Up

Capital Markets

51-250

Founded 2017

View All Jobs 82

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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