Deskripsi Pekerjaan
Are you a passionate PhD candidate looking to apply cutting-edge machine learning research to global-scale fintech challenges? ByteDance is seeking a Machine Learning Engineer Intern to join our Global Payment team in Singapore for a 2026 start. In this role, you will be at the heart of our payment ecosystem, working on transaction processing, fraud detection, and payment optimization platforms that power ByteDance's suite of global products.
As part of our high-impact engineering team, you will dive into complex architectural problems, leveraging state-of-the-art deep learning and statistical modeling to enhance payment efficiency and user experience. This internship offers a unique opportunity to bridge the gap between academic research and real-world implementation, providing you with mentorship from industry leaders and exposure to massive datasets in a fast-paced, innovative environment.
Tanggung Jawab
- Design and implement scalable machine learning models to improve payment conversion rates and transaction security.
- Collaborate with cross-functional teams to identify and resolve complex engineering challenges within the Global Payment infrastructure.
- Analyze large-scale transactional data to uncover patterns and actionable insights for product optimization.
- Develop and maintain robust data pipelines to support model training, evaluation, and deployment.
- Conduct cutting-edge research on deep learning, reinforcement learning, or graph neural networks applied to fintech.
- Proactively identify and mitigate risks related to fraud and anomalous payment activity.
- Document research findings and technical designs to ensure knowledge sharing across the engineering organization.
Kualifikasi
- Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field.
- Strong theoretical foundation in machine learning, deep learning, or optimization algorithms.
- Proficiency in programming languages such as Python, C++, or Java.
- Experience with deep learning frameworks such as PyTorch or TensorFlow.
- Solid understanding of data structures, algorithms, and system design principles.
- Proven ability to translate academic research into practical, scalable software solutions.
- Excellent analytical, problem-solving, and communication skills.
- Ability to thrive in a highly collaborative and dynamic global environment.