Senior Applied Scientist
Tasks
- Apply responsible AI and privacy preserving ML
- Build knowledge retrieval for agentic AI systems
- Build semantic dense and sparse retrieval systems
- Define offline and online evaluation metrics
- Design and run retrieval experiments
- Develop multi stage ranking and retrieval optimization
- Develop retrieval pipelines and models
- Develop retrieval-augmented generation systems
- Establish evaluation frameworks and success metrics
- Implement hybrid dense and sparse retrieval
- Implement personalization and contextual ranking
- Lead and mentor scientists and engineers
- Publish retrieval and ranking research
- Translate product requirements into scalable retrieval infrastructure
Perks/Benefits
- N/A
Skills/Tech-stack
ColBERT | Contextual Ranking | Dense retrieval | Embedding Model | Embedding Model Fine Tuning | Fine Tuning | Hybrid retrieval | Information Retrieval | Language Models | Large Language Models | Late Interaction | Latency optimization | Machine Learning | Model Fine-tuning | Multi-stage ranking | Offline evaluation | Online Experimentation | Personalization | Privacy-preserving | Privacy-preserving machine learning | PyTorch | Python | Query Understanding | RAG | Ranking | Recommender Systems | Reinforcement Learning | Representation Learning | Responsible AI | Retrieval | Retrieval-Augmented Generation | SPLADE | Scalability | Semantic Retrieval | Serving Infrastructure | Sparse Retrieval
Education
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