Senior / Lead Data Scientist (Gen AI)

Conversational AI & Call Transcription Development • Develop and fine-tune automatic speech recognition (ASR) models • Implement language model fine-tuning for industry-specific language. • Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications • Build summarization models to extract key insights from conversations. • Implement Named Entity Recognition (NER) to identify key topics. • Apply LLMs for conversation analytics and context-aware recommendations. • Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support • Develop sentiment and intent classification models. • Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability • Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. • Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. • Implement MLOps workflows to continuously improve model performance with new call data. Technical Skills • Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. • Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. • Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. • Experience with LLM fine-tuning, RAG-based architectures, and LangChain. • Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. • Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills • Ability to translate AI insights into business impact. • Strong problem-solving skills and ability to work in a fast-paced AI-first environment. • Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications • Experience in healthcare, pharma, or life sciences NLP use cases. • Background in knowledge graphs, prompt engineering, and multimodal AI. • Experience with Reinforcement Learning (RLHF) for improving conversation models. Skills Required ASR, Nlp, Python, Pytorch, Tensorflow, Docker