Expert Algorithm Engineer, Paid Ads

SHOPEE IP SINGAPORE PRIVATE LIMITED; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading e-commerce platform in Singapore seeks a professional to lead the development of large-scale Ads systems. The role requires expertise in machine learning and experience with various algorithms, as well as a minimum of 6 years in related systems. Candidates should have strong problem-solving skills and the ability to integrate machine learning solutions effectively.

Qualifications

• Minimum 6 years of experience with search/recommendation/ads systems.
• Experience deploying models in user growth and recommendation projects.
• Knowledge of feature engineering and model training.

Responsibilities

• Lead development of large-scale Ads system.
• Design and implement machine learning models.
• Collaborate with cross-functional teams for integration.

Skills

Machine learning algorithms

Data analysis

Problem-solving

Causal inference techniques

E-commerce domain experience

Education

Bachelor's degree in Computer Science or related field

Tools

TensorFlow

PyTorch

Python

Spark

Hive

Job description

About the team

Established in 2016, the Shopee Advertising Team is responsible for the commercial monetisation of Shopee’s advertising across all its markets. Based in Singapore and Beijing, our team consists of members from renowned global internet companies and prestigious universities. Our primary mission is to support the company’s long-term commercial growth while balancing user experience with effective monetization. Our key tasks include building real-time data feedback systems, developing large-scale distributed advertising services, creating leading predictive models, and establishing healthy advertising mechanisms. We maintain a strong learning and sharing culture and invite passionate, self-driven individuals to join us in our continuous innovation and commitment to serving global users effectively.

The algorithm team aims to serve advertisers and users on the e-commerce platform to meet ads sellers’ business indicators and improve buyers’ engagement. By cooperating with sellers and buyers, we aim to provide high-quality personalized & relevant ads results for Shopee buyers and improve sellers’ ads exposure and sales.

Our team is at the forefront of developing cutting-edge machine learning solutions to improve matching and monetisation efficiencies. We work on a diverse range of ads placements, offering our team members the opportunity to broaden their skills and knowledge in multiple areas.

Job Description:

• Lead and participate in the development of a large-scale Ads system
• Build industry-leading algorithms to improve ads pipelines for paid ads, including recall/pre-rank/ranking etc.
• Involved in the design, development and maintenance of machine learning training data jobs for advertising.
• Design and implement, deliver machine learning models to production to ensure our algorithms give real impact to ads business.
• Research and develop Ads Bidding algorithms, ads traffic control, etc
• Responsible for leading the design and implementation of algorithms focused on user acquisition, activation, and retention for both new and existing customers.
• Collaborate with cross-functional teams, including software engineers, product managers, to integrate machine learning/strategy solutions into the production.

Requirements:

• Bachelor's degree or higher in Computer Science, Data Science, Machine Learning, or a closely related field.
• Minimum of 6 years of experience with search/recommendation/ads systems and various machine learning algorithms, especially for matching/ranking models, such as DESCN, DIN, MMoE.
• Experienced with deploying models at scale focused on user growth and recommendation projects within the E-commerce Domain
• Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, etc. And experience with LLM libraries, such as hugging face, vLLM, etc.
• Knowledge of large scale data analysis, feature engineering, and model training/evaluation/distill/finetune/deployment.
• Skilled in applying causal inference techniques and building uplift models to optimize marketing strategies and user engagement.
• Excellent problem-solving and analytical thinking abilities, with a focus on delivering practical and scalable solution
• Familiar with Python, Spark, Hive, Tensorflow, etc.