Machine Learning Graduate (E-Commerce Governance)-2026 Start (BS/MS)

Team Introduction:

We are the Governance & Experience Algorithm Team — a trailblazing AI force at the forefront of building a trusted, efficient e-commerce ecosystem. Established in 2020, we leverage Graph Neural Networks, Multi-Objective Optimization, Time Series Prediction, and Large Language Models (LLM) to tackle some of the most complex challenges in e-commerce.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with ByteDance.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to ByteDance and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities:

1. Lead Cutting-Edge AI Projects
   • Build graph-powered risk networks to uncover similar product clusters and high-risk seller/creator groups in emerging markets, reducing false advertising incidents in global regions.
   • Develop LLM-based multi-modal systems using cross-modal fusion (text, images, behavioral data) to detect false advertising and low-quality products. Deploy AI-powered product business suggestions to improve seller compliance and user trust.
   • Lead time-series forecasting innovation for logistics performance metrics (e.g., delivery delays, cancellation rates), driving improvement in the e-commerce experience through predictive analytics.
2. Solve Complex Business Challenges
   • Develop multi-task models using MMoE and dynamic loss functions, driving measurable improvements in platform product, service, and logistics health.
   • Transform supply chains by optimizing warehouse product quality qualification strategies to cut missing recalls and reduce warehouse costs.
   • Unleash RPD/RPR growth through causal inference frameworks, identifying hidden correlations between CCR and user behavior to design personalized recommendations.
3. Redefine Industry Standards
   • Optimize LLM reasoning with DPO/GRPO to enhance fraud detection, outperforming traditional SFT methods. Enhance tabular data modeling for better explainability in e-commerce risk assessments.
   • Construct heterogeneous graphs modeling product - seller - creator - video - user relationships, enabling improvements in product lifecycle insights and detection of similar product patterns.
   • Build unified time-series forecasting models across products, sellers, creators, videos, and users, achieving SOTA performance in predicting inventory shortages and demand surges.

Qualifications:

Minimum Qualifications

• Bachelor's degree or above in computer science or related field
• Proficient in Python/C++ and machine learning frameworks (PyTorch/TensorFlow)
• Deep experience with graph neural networks, time series analysis, or LLM
• Track record of delivering AI solutions with measurable business impact
• Passion for tackling ambiguous challenges and translating ideas into scalable solutions

Preferred Qualifications

• Strong communication skills to collaborate cross-functionally and influence stakeholders
• Experience in anti-fraud, prediction/forecasting, e-commerce governance, or related fields