AI / ML Engineer
Tasks
- Build RAG pipeline
- Compute confidence scoring
- Design evaluation test suites
- Develop evaluation framework for agents
- Implement data quality management
- Implement intent routing
- Implement prompt architectures
- Integrate LLMs
- Optimize latency and token cost
- Orchestrate workflows with state and tools
- Process document ingestion pipelines
Perks/Benefits
- N/A
Skills/Tech-stack
Asynchronous programming | Classification | Confidence scoring | Embeddings | Error Handling | FastAPI | Few-Shot Prompting | Few-shot | Human-in-the-loop | Hybrid search | JSON | LLM orchestration | Langchain | Langgraph | Language Models | Large Language Models | OpenTelemetry | PGVector | Pinecone | Prompt engineering | Promptfoo | Python | Ragas | Retrieval-Augmented Generation | Sentence Transformers | Streaming | The Loop | Threshold Calibration | Tiktoken | Token Caching | Transformers | Type Hints | Vector Database | Weaviate
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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