About the Job
Key responsibilities:1. Set up and configure STT (speech-to-text) tools
2. Preprocess and normalize call recordings in Hindi, English, and Hinglish
3. Optimize ASR models for noise, call center artifacts, and diarization or speaker detection
4. Batch transcribe audio files and align with call metadata
5. Assess transcription quality using WER and manual audits and implement improvements
6. Fine-tune and deploy transformer-based models for customer-agent sentiment analysis, fulfillment or resolution prediction, intent classification, and tonality classification
7. Build modular pipelines using LangChain, LlamaIndex, or Haystack for agentic and RAG workflows
8. Implement Retriever-Augmented Generation flows for personalized feedback or call handling logic
9. Develop LLM agents for conversational understanding and rule-based scoring
10. Integrate LLM APIs like OpenAI, Cohere, and Azure OpenAI to summarize conversations, extract structured insights such as intent, outcome, tone, and emotion, and conduct multi-turn dialogue analysis
11. Demonstrate experience with Whisper or other STT tools for transcript handling
12. Show exposure to speech emotion recognition and paralinguistic features
13. Apply background in customer experience analytics or contact center AI
14. Execute models using GPU-based infrastructure
15. Work with diarization and speaker detection techniques
16. Utilize call center datasets or customer support audio for training and analysis
Number of Openings
2 openingsPerks of this Jobs
5 days a week
Skills
Generative AI Tools, Python
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