GNN Graph Neural Network Developer Intern (Remote, Unpaid)

Graph Neural Network (GNN) Developer Internship (Remote, Unpaid)

Company Overview:At Lillup, we are driven by innovation, creativity, and a passion for technology. As a leading tech company, our mission is to develop cutting-edge solutions that make a significant impact in the digital world. We are committed to fostering a culture of learning and growth, offering unique opportunities for aspiring professionals to work alongside our team of experts. Joining Lillup means becoming part of a dynamic environment where your contributions matter, and where you can hone your skills on real-world projects. We are excited to see you grow with us.

Internship Overview:Lillup is seeking an enthusiastic and talented Graph Neural Network (GNN) Developer Intern to join our team. This internship offers a unique opportunity to gain hands-on experience in developing and implementing GNN algorithms and models. You will be contributing to projects that involve the application of GNNs in areas such as recommendation systems, knowledge graph analysis, and data-driven decision-making systems. The ideal candidate will have a passion for machine learning and a strong interest in the application of GNNs to solve complex problems.

Key Responsibilities:Develop and Implement GNN Models: Assist in the design, development, and implementation of Graph Neural Network models for various applications, including recommendation systems, graph-based data analysis, and more.Data Preprocessing: Prepare and preprocess large-scale graph data for input into GNN models, ensuring high-quality data integrity and compatibility.Algorithm Optimization: Work on optimizing and fine-tuning GNN algorithms to improve performance, scalability, and accuracy.Research and Development: Stay up-to-date with the latest research in GNNs and machine learning, applying new techniques and methodologies to ongoing projects.Collaborative Projects: Work closely with data scientists, AI engineers, and software developers to integrate GNN models into larger AI-driven systems.Performance Monitoring: Assist in monitoring and evaluating the performance of GNN models, troubleshooting and resolving issues as they arise.Documentation: Maintain detailed documentation of all model development, performance testing, and implementation processes.

Qualifications:Currently pursuing or recently completed a degree in Computer Science, Machine Learning, Data Science, Mathematics, or a related field.Strong understanding of graph theory, neural networks, and machine learning principles.Familiarity with GNN frameworks and libraries such as PyTorch Geometric, DGL, or Graph Nets.Programming proficiency in Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch).Strong problem-solving skills and the ability to work with complex data structures.Excellent written and verbal communication skills.Ability to work independently and as part of a remote team.

Nice to Have:Experience working with large-scale graph datasets (e.g., social networks, knowledge graphs).Knowledge of unsupervised learning and semi-supervised learning techniques.Familiarity with distributed computing frameworks (e.g., Apache Spark, Dask).Experience with reinforcement learning and its applications to graph-based problems.

We Offer:A unique opportunity to work with cutting-edge GNN technologies and contribute to innovative AI projects.A dynamic and collaborative work environment where your ideas and contributions are valued.Flexible working conditions and the chance to work remotely.A challenging role that offers significant opportunities for professional growth and development.

Next Steps:If you're passionate about machine learning and excited to work on groundbreaking projects involving Graph Neural Networks, we encourage you to apply. Please submit your resume and a detailed cover letter outlining your experience and why you're interested in this internship.

Please Note: This is an unpaid internship, intended primarily for educational and practical experience. There is no guarantee of employment at the conclusion of the internship.

How to Apply:Interested applicants should submit a resume along with a cover letter explaining their interest in GNN development, machine learning, and technology, and why they believe they are a good fit for this internship at Lillup.

Key Skills

• AWS
• Python
• Machine Learning