Machine Learning Engineer

Want to help us help others? We’re hiring!

GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

Join us! The GoFundMe team is searching for our next Senior Machine Learning Engineer to help design and implement our next generation of machine learning solutions powering search and retrieval, recommendation, and personalization systems. You will collaborate with an accomplished and motivated team of individuals to deliver high-impact solutions for our users and our business.

Candidates considered for this role will be located in Buenos Aires. There will be an in-office requirement of 3x a week.

The Job…

• Design and implement AI/ML systems across personalization, recommendations, content understanding, fraud detection, next-best-action services, and more, including batch inference pipelines and real-time applications.
• Design and contribute to the development of taxonomy and ontology structures and content understanding, classification, and tagging systems that provide the foundational signals for discovery, personalization, and recommendations across the company.
• Partner with product and platform stakeholders to define and evolve catalogs, taxonomies, and entity understanding that improve discovery, relevance, and user experiences.
• Design and apply graph-based techniques—such as graph databases, knowledge graphs, and graph algorithms/models—to enhance retrieval, recommendations, personalization, and content understanding.
• Develop and deploy robust, fault tolerant, high-throughput services, emphasizing reliability, scalability, observability, and low-latency performance.
• Lead initiatives to optimize the performance and quality of ML systems using new or established offline and online metrics (e.g., relevance, ranking quality, coverage/diversity, engagement, and long-term user value).
• Support operational excellence by participating in initiatives to streamline ML workflows and establish standardized procedures to ensure consistent and high-quality outcomes across our projects and systems.
• Collaborate closely with AI/ML engineers and cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders, to foster a culture of collaboration, scientific inquiry, and continuous learning.
• Employ a diverse set of tools and platforms, including Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, and GitHub, to develop, deploy, and maintain scalable and robust machine learning systems.