Research Fellowship (Applied AI/ML)
Tasks
- Build LLM as judge rubrics
- Correlate audio stt llm tool and tts traces
- Create adversarial conversational datasets
- Design audio native evaluation frameworks
- Generate fine tuning data and prompt updates
- Implement end-to-end observability
- Mine production traces for failure patterns
- Validate fixes using adversarial replay
Perks/Benefits
- Access to Real Enterprise Data
- Chai Coffee
- Coauthorship opportunities
- Flexible work environment
- Free Lunches
- Mentorship
Skills/Tech-stack
Adversarial Testing | Agentic tool use | Automatic Speech Recognition | Data Mining | Data Pipelines | Dataset Synthesis | Evaluation Frameworks | Fine Tuning | LLM Reasoning | LLM Reasoning Tracing | LLM-as-judge | Language Models | Language Processing | Large Language Models | Machine Learning | Model Fine-tuning | Natural Language | Natural Language Processing | Observability | OpenTelemetry | Prompt engineering | Python | Speech Processing | Speech Recognition | Streaming Data | Streaming data pipelines | Tool use
Education
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