2 days ago

Senior Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Design and implement next-generation ML solutions that power GoFundMe search and retrieval, recommendations, and personalization. You’ll build batch inference and real-time services, develop taxonomy/ontology and entity understanding, and apply graph-based techniques (graph databases and knowledge graphs). Partner with product and platform stakeholders to improve discovery and relevance, while optimizing offline/online metrics and production reliability using Python, AWS, and modern ML infrastructure.

Location: Buenos Aires

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and implement AI/ML systems across personalization, recommendations, content understanding, fraud detection, and next-best-action services, including batch inference and real-time applications.
•Develop taxonomy and ontology structures plus content understanding, classification, and tagging systems that power discovery, personalization, and recommendations.
•Partner with product and platform stakeholders to define and evolve catalogs, taxonomies, and entity understanding to improve relevance and user experiences.
•Apply graph-based techniques (graph databases, knowledge graphs, and graph algorithms/models) to enhance retrieval, recommendations, and personalization.
•Develop and deploy reliable, fault-tolerant, high-throughput services and lead initiatives to optimize ML performance and quality using offline and online metrics.

Pay and Benefits

Perks:Health InsuranceParental Leave

Key Requirements

•4+ years of hands-on experience in machine learning or applied ML engineering, with experience deploying solutions into production environments.
•Experience with search and retrieval (ranking/relevance) and/or recommendation and personalization systems, ideally applied end-to-end for discovery.
•Design, develop, and deploy end-to-end ML systems including data pipelines, feature engineering, model training/serving, and monitoring.
•Experience with catalogs, taxonomies, entity resolution, and embeddings/semantic representations to improve retrieval and recommendation quality.
•Familiarity with graph databases and knowledge graphs, including applying graph algorithms/models to support retrieval and personalization use cases.

Experience:Machine learningSearch and retrievalRecommendationsPersonalization

Skills:CommunicationCollaborationProject scopingContinuous improvementKnowledge sharing

Languages:English

Tech Stack:PythonAWSDatabricksDockerKubernetesFastAPITerraformSnowflakeGitHub

Company Brief

Go Fund Me

Operates an online crowdfunding platform that enables individuals and organizations to raise money for personal causes, medical expenses, charities, and community projects through donations from the public.

Industry: Online Marketplaces

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Headquarters: San Diego, United States

Founded: 2010

Website LinkedIn

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Go Fund Me

2 days ago

Senior Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: Buenos Aires

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and implement AI/ML systems across personalization, recommendations, content understanding, fraud detection, and next-best-action services, including batch inference and real-time applications.
•Develop taxonomy and ontology structures plus content understanding, classification, and tagging systems that power discovery, personalization, and recommendations.
•Partner with product and platform stakeholders to define and evolve catalogs, taxonomies, and entity understanding to improve relevance and user experiences.
•Apply graph-based techniques (graph databases, knowledge graphs, and graph algorithms/models) to enhance retrieval, recommendations, and personalization.
•Develop and deploy reliable, fault-tolerant, high-throughput services and lead initiatives to optimize ML performance and quality using offline and online metrics.

Pay and Benefits

Perks:Health InsuranceParental Leave

Key Requirements

•4+ years of hands-on experience in machine learning or applied ML engineering, with experience deploying solutions into production environments.
•Experience with search and retrieval (ranking/relevance) and/or recommendation and personalization systems, ideally applied end-to-end for discovery.
•Design, develop, and deploy end-to-end ML systems including data pipelines, feature engineering, model training/serving, and monitoring.
•Experience with catalogs, taxonomies, entity resolution, and embeddings/semantic representations to improve retrieval and recommendation quality.
•Familiarity with graph databases and knowledge graphs, including applying graph algorithms/models to support retrieval and personalization use cases.

Experience:Machine learningSearch and retrievalRecommendationsPersonalization

Skills:CommunicationCollaborationProject scopingContinuous improvementKnowledge sharing

Languages:English

Tech Stack:PythonAWSDatabricksDockerKubernetesFastAPITerraformSnowflakeGitHub

Company Brief

Go Fund Me

Industry: Online Marketplaces

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Headquarters: San Diego, United States

Founded: 2010

Website LinkedIn