Graph Machine Learning Engineer (Network)

Summary: We are seeking a talented Graph Machine Learning Engineer to join our team and drive the development of innovative graph-based machine learning models. The ideal candidate will leverage their expertise to solve complex problems and enhance our data-driven decision-making capabilities.

Responsibilities:

• Design and implement graph neural network models to extract insights from large datasets.
• Collaborate with cross-functional teams to integrate graph machine learning solutions into existing systems.
• Develop scalable algorithms for graph data processing and analysis.
• Perform data pre-processing and feature engineering to ensure high-quality model inputs.
• Stay up-to-date with the latest trends and advancements in graph machine learning.
• Conduct experiments to evaluate model performance and refine algorithms as necessary.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Proven experience in machine learning, with a focus on graph-based methods.
• Strong programming skills in Python and familiarity with libraries such as TensorFlow, PyTorch, or similar.
• Knowledge of graph databases and query languages (e.g., Neo4j, Cypher).
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills to convey complex technical concepts to non-technical stakeholders.