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, 3 weeks ago

Cyprus

Full-time

Senior

Machine Learning Engineer

Data Science and Analytics

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

Apply Now

Fundraise Up

Capital Markets

51-250

Founded 2017

View All Jobs 82

Description

Develop and deploy ML solutions across different business areas, including tabular-data use cases such as uplift modeling and recommender systems.
Select appropriate ML or LLM approaches, or propose alternative solutions when they are more effective.
Build end-to-end ML systems, 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 across an internal ML service that supports 10+ product teams and contributes to multiple product areas.
Optimize business outcomes such as donation amounts, upsell offers, admin-panel assistance, and transaction classification.

Requirements

5+ years of ML or data science experience solving real product problems.
Strong knowledge of classical machine learning and mathematical statistics, especially gradient boosting.
Understanding of modern NLP and LLM approaches, including generation, classification, and agents.
Metrics-driven mindset with ability to connect ML metrics such as ROC-AUC, F1, and RMSE to business metrics such as CR and LTV.
Strong Python development skills with a product-oriented approach, clean code, design patterns, and solid engineering practices.
Advanced SQL skills and ability to build complex datasets in ClickHouse independently; experience with MongoDB.
Hands-on MLOps experience with experiment tracking tools and production workflows such as Docker, Git, and CI/CD.
Ability to break down problems, choose the right tech stack, and deliver solutions to production independently.
Strong English required at B2 level; the team primarily communicates in Russian.
Experience with RL is a plus.
Experience with e-commerce mechanics is a plus.
Familiarity with tools in the current stack such as FastAPI, Pydantic, CatBoost, CausalML, OpenAI, MLflow, Airflow, Grafana, Sentry, pandas, Polars, and Redis is a plus.

Benefits

31 days off.
100% paid telemedicine plan.
Home office setup assistance, including support for office furniture and equipment.
English learning courses.
Relevant professional education support.
Gym or swimming pool benefit.
Co-working support.
Remote working option.
Equity options and a long-term focus on sustained contribution.

Interested in this position?

Apply directly on the company website

Apply Now

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