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GoFundMe

Online crowdfunding platform for personal campaigns

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBuenos Aires, ArgentinaNo salary listed

About the Job

Requirements

  • At least four years of hands-on experience in machine learning, applied machine learning engineering, data science, or related fields, emphasizing practical engineering applications and deploying robust solutions into production environments.
  • Extensive experience with one or more of search and retrieval systems, including ranking and relevance; recommendation systems; and personalization systems. Combining these capabilities into end-to-end discovery experiences is a plus.
  • Experience designing, developing, and deploying end-to-end machine learning systems, including data pipelines, feature engineering, model training and serving, and monitoring solutions.
  • Experience with catalogs, taxonomies, entity resolution, embeddings, or semantic representations used to improve retrieval and recommendation quality.
  • Familiarity with graph databases and knowledge graphs, including modeling entities and relationships, building graph-powered features, applying graph algorithms, or graph machine learning, to support retrieval, recommendation, and personalization use cases.
  • Ability to guide projects and foster a collaborative work environment that values continuous improvement and knowledge sharing.
  • Ability to break down complex projects, scope and sequence work, and manage timelines to ensure timely delivery of machine learning initiatives.
  • Verbal and written communication skills to convey complex technical concepts to technical and non-technical stakeholders.

Responsibilities

  • Design and implement artificial intelligence and machine learning systems across personalization, recommendations, content understanding, fraud detection, next-best-action services, and other areas, including batch inference pipelines and real-time applications.
  • Design and contribute to taxonomy and ontology structures and content understanding, classification, and tagging systems that provide 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 to improve discovery, relevance, and user experiences.
  • Design and apply graph-based techniques, such as graph databases, knowledge graphs, and graph algorithms or 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 machine learning system performance and quality using offline and online metrics such as relevance, ranking quality, coverage and diversity, engagement, and long-term user value.
  • Participate in operational-excellence initiatives to streamline machine learning workflows and establish standardized procedures for consistent, high-quality outcomes across projects and systems.
  • Collaborate with artificial intelligence and machine learning engineers and cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders, to foster collaboration, scientific inquiry, and continuous learning.
  • Use Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, and GitHub to develop, deploy, and maintain scalable, robust machine learning systems.

Desired Qualifications

  • An advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, Data Science, or a related technical field is preferred.
  • Experience combining search and retrieval, recommendation, and personalization capabilities into end-to-end discovery experiences is a plus.

About the Company

GoFundMe

Online crowdfunding platform for personal campaigns

GoFundMe is an online fundraising platform that helps individuals and organizations raise money for a wide range of needs and dreams, such as medical emergencies, memorial funds, education, and nonprofit support. Users start a fundraiser in about five minutes, tell their story, and share a link to collect donations from their network and beyond. Contributions are made through a secure online payment system, and GoFundMe earns revenue mainly from voluntary donor tips and a small transaction fee on each donation. The platform emphasizes safety and ease of use to ensure a positive experience for both donors and recipients. Compared with others, GoFundMe has built a global community of tens of millions of people and hundreds of millions of donations, which helps campaigns reach a larger audience. Its main goal is to mobilize communities to provide financial assistance and support when people need it most.

Company size
1,001-5,000
Company stage
Series A
Total funding
$1.2B
Headquarters
San Diego, CA
Founded
2010

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