About the role

Our Search Team, comprising of Applied Scientists and Software Engineers, specializes in Machine Learning. We work together to build custom machine-learning models that can drive product vision and customer impact. We are looking for individuals who are product driven, and are passionate about making ML innovations in areas such as Ranking, Optimization, Natural Language Processing, Information Retrieval, Graph Learning, Reinforcement Learning to help improve the StockX buyer/seller search experience!

Example Projects:

• Develop powerful embeddings to collect salient signals of our customers, product, and user interactions.
• Extract real-time signals and multi-modality data (i.e, content and image) from our 5M+ product catalog images and 1M+ listings. Understand semantic content, aesthetic style, materials for ranking and optimization.
• Build the first personalized search ranking and real-time in-session personalization.
• Implement and compare supervised learning models (i.e, LR, GBDT, and DNNs) or ensembles of models, to improve metrics, often with multiple contending objectives (i.e, relevance, degree of personalization, average value of orders, repeated frequencies/purchases).
• Develop models with custom architecture or objective functions that target StockX-specific problems, such as personalized search, revenue optimization, seller fairness, seasonality, etc.
• Develop brand-new learning frameworks for query suggestions to understand buyer experience.

What you'll do

• Apply the latest advances in deep learning and machine learning to improve buyer and seller experiences on StockX.
• Prototype, optimize, and productionize large-scale ML models that help deliver key results in search experience.
• Conduct A/B experiments to validate ML models and pipelines.
• Work closely with product managers, ML scientists/engineers, full-stack engineers, and designers on product teams to deliver content to tens of millions of users.

About you

• Experience with object-oriented or functional software development
• Experience working with AWS or other cloud providers
• Experience with big data platforms like Spark
• Experience with machine learning libraries such as TensorFlow, PyTorch, or MXNet
• You have dealt with data exploration, analysis, and feature engineering
• You have relentlessly high standards for the products you deliver
• Work effectively in an agile development process

Bonus points:

• You have a Ph.D. degree in Computer Science or related engineering fields, or 5+ years of practical machine learning experience.
• You have published at peer-reviewed conferences, such as ICML, KDD, SIGIR, WSDM, etc. or  you have given talks/tutorials in the industrial conferences like Spark Summit. 
• You have experience using AWS Cloud Platform.
• You have experience in building production search, recommendations, advertising, or general e-commerce systems.