Machine Learning Engineer (Payment & Risk) - Global Payment - Singapore

PIPO RESOURCE (SG) PTE. LTD.

Singapore

On-site

SGD 120,000 - 200,000

Full time

3 days ago
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Benefits offered by this job

Stock options
Positive team atmosphere
Career growth
Paid leave
Flat organization
100+ mil users
Industry experts

Job summary

ByteDance Singapore is seeking a skilled ML engineer to support the Global Payments and Compliance teams. You will refine fraud detection models, build scalable risk assessment tools, and collaborate with data scientists and engineers to secure payments across platforms.

Ideal candidates have a CS/Math background, strong programming skills in Python/Java/C++, and experience with ML frameworks like TensorFlow or PyTorch. Join a fast-growing tech company committed to innovation and impact.

Qualifications

  • Bachelor's degree or higher in computer science, engineering, statistics, applied mathematics, or related fields.
  • Solid experience with data structures and algorithms.
  • Familiar with TensorFlow / PyTorch / MXNet and their training/deployment details.
  • Strong coding skills in Python, Java, or C/C++.

Responsibilities

  • The Global Payment team provides payment solutions including acquisitions, disbursements, transaction monitoring, payment method management, FX conversion, accounting, and reconciliations to ensure a smooth, secure user experience across ByteDance platforms.
  • The Global Payments Compliance team establishes a strong compliance foundation with sanction screening, monitoring, risk rating, and governance.
  • Refine fraud detection feature engineering and risk evaluation systems;
  • Develop universal fraud and account takeover (ATO) detection models for global payment scenarios;
  • Explore sequence models, graph networks, and LLMs in risk control contexts;
  • Develop ML models to identify cross-border and regional payment risks from a global perspective;
  • Optimize modeling workflows to improve development and deployment efficiency and reduce maintenance costs;
  • Research and apply cutting-edge ML algorithms within risk control domain.

Skills

Data structures & algorithms
TensorFlow/PyTorch/MXNet
Programming: Python/Java/C/C++

Education

Bachelor's degree in CS/CE/Math/Data Science

Tools

TensorFlow
PyTorch
MXNet

Job description

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.

Why Join ByteDance

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.

As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Job highlights
  • Stock options
  • Positive team atmosphere
  • Career growth opportunity
  • Paid leave
  • Flat organization
  • 100+ mil users
  • Industry experts
Responsibilities
  • The Global Payment team of Bytedance provides payment solutions - including payment acquisitions, disbursements, transaction monitoring, payment method management, foreign exchange conversion, accounting, reconciliations, and so on to ensure that our users have a smooth and secure payment experience on ByteDance platforms.
  • The Global Payments Compliance team's duty is to establish a comprehensive and strong compliance foundation with sanction screening, transaction monitoring, risk rating system to systematically enable business models, revenue growth, and protect executives from possible legal liabilities for Bytedance.
  • Refine payment risk feature engineering and fraud evaluation systems;
  • Develop universal fraud and account takeover (ATO) detection models for global payment scenarios;
  • Explore the application of sequence models, graph networks, and LLMs in risk control scenarios;
  • Develop universal machine learning models to identify cross-border and regional payment risks from a global perspective;
  • Optimize modeling workflows to improve development/deployment efficiency and reduce maintenance costs;
  • Research and apply cutting-edge machine learning algorithms within the risk control domain.
Qualifications
Minimum Qualifications
  • Bachelor's degree and above with majors in computer science, computer engineering, statistics, applied mathematics, data science or other related disciplines;
  • Solid experience with data structures and algorithms;
  • Familiar with at least one framework of TensorFlow / PyTorch / MXNet and its training and deployment details;
  • Strong coding skills in at least one of the following programming languages, e.g. Python, Java, C/C++.
Preferred qualifications
  • Minimum 3 years of relevant experience
  • Minimum 3 years of relevant experience;
  • Experience in NLP, graph mining, or fraud detection;
  • Experience in credit risk, payment risk, or search/recommendation systems;
  • CCF A/B Papers or competition awards are preferred
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