Machine Learning Engineer - Search & Recommendations

Machine Learning Engineer - Search & Recommendations

This job is no longer open

Why you'll love this role

Our AI/ML Team is on a mission to build the next-generation e-commerce platform for the next generation customer. We build world-class, innovative experiences and products that give our users access to the world’s most coveted products and unlock economic opportunity by turning reselling into a business for anyone. Our team uses cutting edge technologies that handle massive scale globally. We’re an internet-native, cloud-native company from day 1 - you won’t find legacy technology here. If you’re a curious leader who loves solving problems, wearing multiple hats, and learning new things, join us!

In the Search & Recommendation team, we work together to productionalize custom machine-learning models that can drive product vision and customer impact at scale. We are looking for MLE 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 experience!

Example Projects:

  • Develop 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 retrieval, ranking and optimization.
  • Build a real-time, in-session personalization recommendation system.
  • 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 recommendation system, 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, Data 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 or Databricks.
  • 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.
  • You have a postgraduate degree in Computer Science or related engineering fields plus 1+ machine learning experience, or 3+ years of practical machine learning experience.
  • Experience with Kubernetes and Docker for productionalizing models.
  • You have experience in building machine learning systems at scale.
  • You have experience in using AWS Cloud Platform and/or OpenSearch.
  • You have experience in building production search, recommendations, advertising, or general e-commerce systems.

 

Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

Pursuant to the various pay transparency laws/acts, the base salary range is $120,000 to $140,000 plus opportunities for benefits (e.g., medical, dental), equity and discretionary bonuses. Compensation is dependent on geography and may vary.

This job is no longer open
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