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

Armenia

Full-time

Senior

Machine Learning Engineer

Data Science and Analytics

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

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 appropriate ML and LLM approaches, or propose alternative solutions when they are a better fit.
Build end-to-end ML systems covering data preparation, 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 projects related to donation optimization, upsell offers, admin panel assistants, transaction classification, and e-commerce mechanics.
Collaborate with internal product teams as an ML center of excellence serving 10+ product teams.
Deliver solutions to production with an emphasis on performance, reliability, and business impact.

Requirements

5+ years of ML or data science experience solving real product problems.
Strong expertise in machine learning and mathematical statistics, including classical algorithms such as gradient boosting.
Understanding of modern NLP and LLM approaches.
Ability to connect ML metrics such as ROC-AUC, F1, and RMSE with business metrics such as CR and LTV.
Strong Python engineering skills with a product-oriented mindset, clean code habits, design patterns, and solid engineering practices.
Advanced SQL skills and the ability to independently build complex datasets in ClickHouse.
Experience working with MongoDB.
Hands-on experience with experiment tracking tools and understanding of production workflows such as Docker, Git, and CI/CD.
Ability to break down problems, choose the right tech stack, and justify non-ML solutions when appropriate.
English at B2 level or higher; Russian-speaking team environment.
Experience with LLMs, RAG, prompt engineering, or fine-tuning is a plus.
Familiarity with the company tech stack, including FastAPI, Pydantic, CatBoost, CausalML, MLflow, Airflow, Grafana, and Sentry, is preferred.

Benefits

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

Interested in this position?

Apply directly on the company website

Apply Now

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