Senior Data Scientist - Generative AI

About the Role :

We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA.

The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making.

The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems.

This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools.

Key Responsibilities :

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.

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.

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.

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.

Qualifications :

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.