Algorithm Engineer, Marketplace Intelligence & Data Computer Vision (campus Recruitment 2026)

Singapore, SG, Singapore

Job Description

Department Engineering and Technology
LevelEntry Level
LocationSingapore
The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.


About the Team:


Shopee will be prioritizing applicants who have a

current right to work in Singapore

, and

do not require Shopee sponsorship of a visa

.
Kindly note that you can only be considered in

one recruitment process at a time within Sea Group

and will be considered for jobs in the order that you have applied.

The Marketplace Intelligence and Data team's mission is to build sustainable and efficient data and intelligence products to facilitate Shopee's business development. The team is responsible for Shopee e-commerce data warehouse construction, merchant and operation data product construction, all-link traffic data, product algorithms, including product release, control, information optimization, SPU library and its comparison business, marketing algorithms, including Merchandising, Product Selection, Recommendation Algorithm, Evaluation Algorithms, User Profiling, and in addition, basic AI capabilities, such as Machine Translation, Speech Algorithm, Image Algorithm, and Real-person Authentication.

:

Develop CV-based identity verification models and services, including: + Anti-spoofing against various attack types (e.g., deepfake);
+ Passive and active liveness checks;
+ OCR for IC cards and identity documents;
+ Anti-spoofing for IC card tampering;
+ On-device and server-side image quality assessment.
Design and implement robust training, inference, and data processing pipelines. Write high quality, elegant, readable, and easy to maintain code. Collaborate with business stakeholders, product managers, and engineering team, and get involved in the entire life cycle of our eKYC solutions, from problem formulation, technical design, to implementation, upgrading, and maintenance.

Requirements:

Bachelor or above in Computer Science, Machine Learning, or relevant majors. Proficient in Python and deep learning framework (e.g., PyTorch) to build custom modules, dataloaders, and training loops. Deep and broad knowledge in at least one of areas: computer vision, multimodel, or vision-language models (VLMs). Familiar with model debugging, dynamic computation graphs, and memory management. Familiar with large-scale model development frameworks (e.g., HuggingFace, LLaMA-Factory) and deployment pipelines (e.g., ONNX, TorchScript). Familiar with model optimization techniques (e.g., pruning, quantization, knowledge distillation) and training efficiency techniques (e.g., mixed precision, distributed training). Good teamworking spirit, positive attitude, self-driven. Good oral and written English, good communication skills. Passionate about technology, fast learner, willing to share.

Good To Have:

Master's or above in Computer Science or relevant Majors. Publications in top-tier computer vision or AI conferences and journals. Prior experience in eKYC, digital identity, fraud prevention or security-related projects. * Prior experience in VLMs/LLMs.

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Job Detail

  • Job Id
    JD1558413
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    Singapore, SG, Singapore
  • Education
    Not mentioned