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Job Description
StockX, a global startup headquartered in the USA with development offices in Bangalore, India, is seeking a Senior Machine Learning Engineer to join their Search & Recommendation team. This role involves productionalizing custom machine-learning models to drive product vision and customer impact at scale. The ideal candidate will be product-driven and passionate about making ML innovations in areas such as Ranking, Optimization, Natural Language Processing, Information Retrieval, Graph Learning, and Reinforcement Learning to improve the StockX buyer/seller experience.
What this role involves:
- Developing embeddings to collect salient signals of customers, products, and user interactions.
- Extracting real-time signals and multi-modality data from product catalog images and listings.
- Understanding semantic content, aesthetic style, and materials for retrieval, ranking, and optimization.
- Building a real-time, in-session personalization recommendation system.
- Implementing and comparing supervised learning models to improve metrics.
- Developing models with custom architecture or objective functions for StockX-specific problems.
- Developing learning frameworks for query suggestions.
- Applying advances in deep learning and machine learning to improve buyer and seller experiences.
- Prototyping, optimizing, and productionalizing large-scale ML models.
- Conducting A/B experiments to validate ML models and pipelines.
- Collaborating with product managers, data scientists/engineers, full-stack engineers, and designers.
Requirements:
- 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.
- Experience with data exploration, analysis, and feature engineering.
- High standards for product delivery.
- Ability to work effectively in an agile development process.
- A postgraduate degree in Computer Science or related engineering fields plus 3+ machine learning experience, or 5+ years of practical machine learning experience.
- Experience with Kubernetes and Docker for productionalizing models.
- Experience in building machine learning systems at scale.
- Experience in using AWS Cloud Platform, Databricks and/or OpenSearch.
- Experience in building production search, recommendations, advertising, or general e-commerce systems.
