Senior Data Scientist
Tasks
- Analyze agent failures and data gaps
- Build LLM powered retrieval pipelines RAG
- Build agentic systems for multi-agent coordination
- Develop reusable agent platform
- Establish offline and live evaluation infrastructure
- Fine tune LLM models for production use
- Prototype improvements to features algorithms and models
- Translate SME domain knowledge into agent instructions
Perks/Benefits
- N/A
Skills/Tech-stack
Agent systems | BERT | CrewAI | Data Pipelines | Feature Engineering | Fine Tuning | KL divergence | LLM-powered | LLM-powered Applications | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | LoRA | Model Evaluation | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | NoSQL | PEFT | Python | RAG | RLAIF | RLHF | Retrieval-Augmented Generation | SQL | Sequence Modeling | Statistical modeling | Supervised Learning | Word Embeddings
Education
Roles
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