Staff / Principal Applied AI Researcher (Agentic Search)
Tasks
- Analyze relevance latency and cost trade offs
- Define evaluation frameworks and metrics for agentic systems
- Deploy systems in high throughput low latency environments
- Design multi stage retrieval architectures
- Develop LLM grounding methods for real time web data
- Drive applied research and technical direction for retrieval and ranking
- Lead experimentation with embeddings hybrid search and reranking
- Mentor engineers
- Own ambiguous problems end to end
Perks/Benefits
- Career growth and learning opportunities
- Collaborative culture
- Flexibility
- High ownership
- International environment
Skills/Tech-stack
Artificial Intelligence | C++ | Embeddings | Evaluation Frameworks | Experimentation | Go | Hybrid search | LLM | Language Models | Large Language Models | Machine Learning | Python | Query Understanding | Query rewriting | RAG | Ranking | Recommendation Systems | Reranking | Retrieval | Search Systems | Transformers
Education
N/A
Regions
Countries
States
Cities
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