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GoFundMe is seeking a Senior Machine Learning Engineer to design and implement next-generation ML solutions powering search, retrieval, recommendations, and personalization systems. The role requires 3 days per week in-office in Buenos Aires.
Key responsibilities include:
- Design and implement AI/ML systems for personalization, recommendations, content understanding, fraud detection, and next-best-action services, including both batch inference pipelines and real-time applications
- Develop taxonomy and ontology structures for content understanding, classification, and tagging that provide foundational signals for discovery and personalization across the platform
- Partner with product and platform teams to define and evolve catalogs, taxonomies, and entity understanding to improve discovery, relevance, and user experiences
- Apply graph-based techniques (graph databases, knowledge graphs, graph algorithms/models) to enhance retrieval, recommendations, and personalization
- Develop and deploy robust, fault-tolerant, high-throughput services emphasizing reliability, scalability, observability, and low-latency performance
- Lead initiatives to optimize ML system performance and quality using offline and online metrics (relevance, ranking quality, coverage/diversity, engagement, long-term user value)
- Support operational excellence by streamlining ML workflows and establishing standardized procedures
- Collaborate with AI/ML engineers, data scientists, software engineers, product managers, and business stakeholders
- Work with Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, and GitHub
Required qualifications:
- 4+ years hands-on experience in machine learning, applied ML engineering, data science, or related fields with emphasis on production deployments
- Extensive experience with search/retrieval systems (ranking, relevance), recommendation systems, and/or personalization systems
- Experience designing, developing, and deploying end-to-end ML systems including data pipelines, feature engineering, model training/serving, and monitoring
- Experience with catalogs, taxonomies, entity resolution, embeddings, and semantic representations
- Familiarity with graph databases and knowledge graphs for retrieval, recommendation, and personalization use cases
- Demonstrated ability to guide projects and foster collaborative, high-performing work environments
- Strong project breakdown, scoping, sequencing, and timeline management skills
- Excellent verbal and written communication for technical and non-technical audiences
- Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, Data Science, or related field preferred
