Data Scientist III
Tasks
- Architect enterprise LLM applications from prototype to production
- Build deploy monitor and iterate machine learning models
- Conduct experimentation using A B and quasi experimental studies
- Create scalable data and ML pipelines with engineering teams
- Define data strategy for structured and unstructured data
- Design agentic workflows and multi step orchestration
- Drive architecture standards and engineering best practices
- Fine tune and adapt foundation models for domain use cases
- Govern vector database and retrieval patterns
- Mentor DS1 and DS2 through reviews and pairing
- Own LLM evaluation and hallucination mitigation
- Present architectures results and recommendations to stakeholders
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | Autogen | Azure | B testing | Bayes | Bayesian Methods | CI/CD | Causal Inference | CrewAI | DeepEval | Docker | Experimentation | Git | Hybrid search | Kubernetes | LLMOps | Langgraph | Language Processing | LoRA | MLOps | Machine Learning | Monitoring | Natural Language | Natural Language Processing | PEFT | Python | QLoRA | Quasi Experimental | RAG | Ragas | Reranking | Responsible AI | SQL | Time Series | TruLens | Vector Database
Education
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