Job Description
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Company Overview
A rapidly growing live-commerce marketplace that enables users to buy, sell, and discover products across a wide range of categories. The company combines live streaming, community, and commerce to help sellers build businesses while creating engaging shopping experiences for buyers.
Responsibilities
- Lead the design, development, and productionization of machine learning models supporting user acquisition, activation, and retention, including ranking models, targeting systems, and uplift modeling.
- Own the end-to-end machine learning lifecycle, including data pipelines, feature engineering, model training, deployment, and online experimentation.
- Develop feedback loops using postbacks, conversion events, and downstream revenue signals to continuously improve machine learning systems.
- Identify and prioritize high-impact opportunities where machine learning can drive buyer growth and improve user experiences.
- Collaborate with product, engineering, data, and marketing teams to translate growth opportunities into scalable ML solutions.
- Develop personalization models designed to improve user retention across acquisition and engagement channels.
- Drive technical excellence and establish machine learning best practices across the growth engineering organization.
- Help improve first-time buyer conversion and expand the overall buyer base through intelligent, data-driven experiences.
Qualifications
- 5+ years of industry experience building and deploying machine learning systems at scale.
- Demonstrated success leading end-to-end machine learning projects that delivered measurable business outcomes.
- Deep expertise in personalization, ranking, or user modeling.
- Strong understanding of user behavior within consumer-facing products.
- Advanced proficiency in Python and SQL.
- Strong experience with common machine learning frameworks such as PyTorch, TensorFlow, or XGBoost.
- Strong communication and leadership skills, with the ability to influence technical roadmaps and align cross-functional teams.
- Ability to work effectively with product, engineering, data, and marketing stakeholders.
- Low-ego, collaborative approach with a growth mindset and strong bias toward action and measurable impact.
Preferred Qualifications
- Experience developing machine learning applications for e-commerce or social products.
- Experience working in growth-focused domains such as user segmentation, retention modeling, large-scale recommendation systems, or notification ranking.
- Experience developing personalization and recommendation systems for consumer products.
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