AI Application Engineer
Tasks
- Build automated model evaluation pipelines
- Build multi-step LLM orchestration pipelines
- Deploy monitor and improve AI applications in production
- Design develop optimize production-grade LLM applications
- Design multi-turn conversational AI experiences
- Ensure AI quality RAG accuracy prompt engineering AI safety
- Implement AI safety guardrails
- Implement optimize RAG pipelines
- Integrate NVIDIA enterprise AI technologies
- Perform latency profiling and optimization
Perks/Benefits
- N/A
Skills/Tech-stack
AI Safety | Async Programming | Automated Evaluation | Chunking | Context Management | Deployment Monitoring | Embeddings | Hallucination detection | Hybrid search | Injection prevention | Jailbreak mitigation | Langchain | Language Models | Large Language Models | Latency optimization | Llamaindex | NVIDIA Nemo | NeMoGuardrails | Nvidia Nim | Prompt engineering | Prompt injection | Prompt injection prevention | Python | RIVA | Regression testing | Release gating | Reranking | Retrieval-Augmented Generation | Session memory | Similarity Search | Topical Control | Vector Databases | Vector similarity | Vector similarity search
Education
N/A
Roles
AI | AI Application Engineer | Application Engineer | Engineer
Regions
Countries
States
Cities
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