Work closely with the promotion product team, business partners, and internal stakeholders to identify marketplace growth challenges, uncover actionable insights, and deliver practical, scalable solutions based on large-scale user and product data.
Collaborate with product and engineering teams to design and build end-to-end machine learning pipelines to power data-driven decision-making for promotions and campaign planning.
Apply cutting-edge AI technologies such as LLMs, Agents, and RL to improve efficiency of building e-commerce campaigns.
Work on core solutions related to personalized recommendations, promotion and voucher configuration optimization, campaign budget planning, and product demand forecasting.
Develop, iterate, and maintain machine learning models, including those based on deep learning, reinforcement learning, and multi-armed bandit frameworks, applied in areas such as recommendation, search, and ads ranking.
Conduct rigorous online and offline evaluations, including A/B testing, to ensure model effectiveness and business impact.

Bachelor's degree or above in Computer Science, Engineering, Mathematics, Statistics, Biostatistics, or related fields.
Proficiency in at least one programming language (e.g., Python, Golang, Scala) and Unix/Linux systems.
Experience working with large datasets and complex data analysis using SQL, Python.
Knowledge of optimization, classical machine learning (classification, regression, clustering), deep learning, and reinforcement learning.
Good understanding of LLMs and agents, having practical project experience is a plus.
Experience with TensorFlow/PyTorch, distributed data processing frameworks (e.g., Hadoop, Spark).
Good communication skills with ability to explain technical content to stakeholders.
Teamwork mindset and ability to collaborate with cross-functional teams.

Algorithm Engineer, SRA - Promotion (2027 Graduate)