Machine Learning Engineer, Personalization and Recommendations
Tasks
- Advance offline evaluation metrics and A B testing
- Build model training evaluation deployment pipelines
- Design and implement personalization models
- Develop retrieval and serving systems
- Evaluate research trends for application
- Mentor engineers in responsible ML practices
- Monitor model reliability training serving consistency drift
- Optimize distributed training and inference in production
- Translate learner objectives into modeling goals
Perks/Benefits
- Access to LinkedIn Learning
- Employer-sponsored 401k
- Health, dental, vision insurance
- Onsite work arrangement
- Paid family leave
- Paid time off
- Wellness benefits
Skills/Tech-stack
A/B | A/B Testing | ANN | AUC | B testing | Calibration | Distributed Training | Drift Detection | Experiment design | Faiss | Feature Engineering | Feature Store | MLOps | Machine Learning | Model Deployment | Model Registry | Monitoring | NDCG | Personalization | PyTorch | Python | Ranking | Recommender Systems | ScaNN | Transformers | Two Tower Models | Two-Tower | Vector Search
Education
N/A
Regions
Countries
States
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