Staff Machine Learning Engineer, Personalization
Tasks
- Build embedding based retrieval pipelines
- Build recommendation ranking systems
- Build scalable offline and online ML platforms
- Build semantic retrieval systems
- Collaborate with product, engineering, and data science teams
- Construct ML training pipelines
- Define model evaluation metrics
- Deploy transformer based models in production
- Design machine learning models
- Develop personalized product discovery
- Drive continuous experimentation
- Ensure model reproducibility
- Ensure model scalability
- Implement query understanding models
- Implement vector search for retrieval
- Mentor engineering talent
- Monitor model impact
- Orchestrate ML workflows
- Serve ML models in real time
Perks/Benefits
- 401k match
- Disability insurance
- Electric Car Charging Station
- Employee assistance program
- Flexible spending account
- Health savings account
- Medical/dental/vision/life insurance
- Paid parental leave
- Paid time off
- Pre-tax commuter benefits
- Public holidays
Skills/Tech-stack
Airflow | Apache Spark | BigQuery | Contrastive Learning | Deep learning | Embeddings | H2O | Information Retrieval | Java | Keras | Kubeflow | LLM | LightGBM | MLflow | Machine Learning | Multi-Modal | Multi-Modal Learning | PyTorch | Python | Recommendation Systems | SageMaker | Scikit-learn | Statistical modeling | TensorFlow | Transformer | Vector Search | Vertex AI | Weights and Biases | XGBoost
Education
Regions
Countries
States
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