Salary
💰 $152,500 - $262,350 per year
Tech Stack
AWSAzureCloudGoogle Cloud PlatformPythonPyTorchScalaScikit-LearnSparkTensorflow
About the role
- Build the next generation of product discovery for millions of global shoppers
- Own backend and data infrastructure powering search, recommendations, and catalog knowledge at global scale
- Contribute to product search stack including indexing pipelines and query-time services
- Collaborate closely with backend engineers and catalog data teams to integrate models and data
- Work on query and document understanding, product entity modeling and enrichment, and taxonomy structuring
- Design and implement retrieval and ranking algorithms and evaluate search quality
- Lead development and optimization of advanced machine learning models
- Oversee preprocessing and analysis of large datasets
- Deploy, maintain, monitor, and iterate on ML solutions in production environments
- Integrate ML models into products and services and evaluate model performance
Requirements
- 5+ years relevant experience (or any equivalent combination of education and experience)
- Bachelor's degree OR equivalent combination of education and experience
- Preferred: 8+ years industry experience with deep learning architectures and production ML models
- Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn
- Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment
- Strong proficiency in Python, Scala, or other programming languages
- Experience working with large datasets and data processing pipelines (e.g., Dataflow, Spark, Flink)
- Experience with scalable architectures
- Experience working on search or recommendation systems at scale
- Familiarity with A/B testing and experimentation methodologies for search relevance improvement
- Strong communication and collaboration skills
- Experience taking projects from research and prototyping to production deployment