Staff / Principal Applied AI Researcher (Agentic Search)
Tasks
- Analyze trade offs across relevance latency and cost
- Define evaluation frameworks and metrics for agentic systems
- Deploy retrieval systems in high throughput low latency environments
- Design multi stage retrieval architectures
- Develop methods for grounding large language models in real time web data
- Drive applied research and technical direction across retrieval and ranking systems
- Lead experimentation on modern retrieval approaches
- Mentor engineers and raise technical bar
- Own ambiguous problems end to end
Perks/Benefits
- Career growth
- Collaborative culture
- Flexibility
- Impactful projects
- International environment
- Learning opportunities
- Ownership
Skills/Tech-stack
C++ | Deep learning | Embeddings | Evaluation | Go | Hybrid search | Information Retrieval | Language Models | Large Language Models | Latency optimization | Machine Learning | Python | Recommendation Systems | Reranking | Retrieval-Augmented Generation | Search & Ranking | Transformers
Education
N/A
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