Machine Learning Engineer

December 28, 2023

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Jumio Corporation

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Identity verification through informed AI.

online ID verification • card scanning • mobile payments • computer vision • credentials management

201 - 500

Description

• Devise and construct cutting-edge graph-based machine learning models and algorithms aimed at detecting and mitigating fraudulent activities within intricate, interlinked datasets • Implement and enhance graph-based algorithms dedicated to node classification, link prediction, and community detection • Collaborate with cross-functional teams to integrate machine learning models into scalable and efficient production systems • Conduct thorough analyses and experiments to evaluate model performance, scalability, and efficiency on graph-based data structures • Research and remain abreast of the latest advancements in graph-based machine learning techniques, contributing groundbreaking concepts to augment our fraud detection technological capabilities

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field • Demonstrated proficiency (3 years) in crafting and deploying machine learning models tailored explicitly for detecting fraud within graph-based data structures • Strong proficiency in graph theory, graph algorithms, and graph databases (e.g., Neo4j, Amazon Neptune, TigerGraph) • Proficient in programming languages commonly used in machine learning (e.g., Python, R, Java) and libraries/frameworks (e.g., NetworkX, PyTorch Geometric, GraphSAGE) • Hands-on experience in data preprocessing, feature engineering, and model assessment within the domain of graph-based machine learning specifically oriented towards detecting fraudulent activities Great to have Experience and Qualifications: • Solid understanding of graph embedding techniques, graph neural networks, and their applications in solving real-world problems • PhD in Computer Science or a related field with a focus on graph-based machine learning • Familiarity with distributed computing frameworks (e.g., Apache Spark) for scalable graph processing • Experience working with large-scale graph datasets and optimizing performance for computational efficiency • Contributions to open-source projects related to graph-based machine learning or graph algorithms • Strong analytical and problem-solving skills with a keen eye for detail in optimizing algorithms for performance and scalability

Benefits

• Work alongside various experts in product and engineering • Contribute to augmenting our fraud detection technological capabilities • Opportunity to work with cutting-edge graph-based machine learning models and algorithms • Collaborate with cross-functional teams • Stay updated with the latest advancements in graph-based machine learning techniques