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Expect depth on ML for risk (ranking, anomaly detection, evaluation under class imbalance), plus clear reasoning on trade-offs between precision, recall, and user friction in e-commerce. Practice explaining research you own end-to-end and how you would productionize it with product partners.
Strong fit if you are a PhD-track researcher who wants applied ML in large-scale e-commerce risk at ByteDance in Singapore starting 2027. Less fit if you want remote work or a purely product-feature engineering path without risk-control modeling.
As a PhD Machine Learning Engineer Graduate on ByteDance’s Global E-Commerce Risk Control track (2027 start), you would frame fraud, abuse, and trust problems as models, prototype detectors, and partner with product and operations to ship controls. Days likely mix literature-backed modeling, offline evaluation, and reviews with managers and adjacent teams—aligned with research-scientist style analysis rather than pure app coding.
No. The listing is for Singapore with remote set to off, so plan for on-site work.
It targets a PhD graduate start in 2027 for ML on global e-commerce risk control, closer to research-scientist style problem solving than general software delivery alone.
Use free or free-to-learn paths such as freeCodeCamp, Saylor CS courses, CS50, and Microsoft Learn developer training—costs match those resources exactly.
Public-domain labor data — prepare examples for 2–3 of these.
Website: bytedance.com
ByteDance is a Chinese internet technology company headquartered in Haidian, Beijing. Its associated variable-interest entity, ByteDance Ltd, is incorporated in the Cayman Islands.
Public cache only — not an employee review.
MACHINE LEARNING ENGINEER GRADUATE (GLOBAL E-COMMERCE, RISK CONTROL) - 2027 START (PHD)ByteDanceSingapore About the Role We are seeking a Machine Learning Engineer Graduate to join our team in Singapore. As part of ByteDance's global e-commerce and risk control initiatives, you will develop domain-specific machine learning models and agents to decode and prevent intricate, cross-domain fraudulent activities. This role involves analyzing massive business and security data to mine abnormal user behavior patterns. Day-to-Day Responsibilities Develop and implement machine learning algorithms for fraud detection and prevention in global e-commerce platforms. Analyze large datasets to identify trends, anomalies, and potential risks associated with user behavior. Create and maintain models that can adapt to new types of fraudulent activities. Collaborate with cross-functional teams to integrate machine learning solutions into existing systems. What We're Looking For A recent PhD graduate in Computer Science, Data Science, or a related field. Strong experience with machine learning frameworks and tools such as TensorFlow, PyTorch, or Scikit-learn. Familiarity with natural language processing (NLP) techniques is a plus. Excellent problem-solving skills and ability to work in a fast-paced environment. About ByteDance ByteDance is a global technology company that aims to inspire creativity and enrich lives worldwide. Our mission is to build products that empower people, and we are committed to fostering an innovative and inclusive workplace culture. How to Apply To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there.
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