Company: Cognitensor

Location: Noida, Uttar Pradesh

Workplace Type: On-site

Employment Type: Full-time

Experience Required: 3 Years

Salary Budget: Up to 15 LPA

About the Role

Cognitensor is looking for a skilled Data Scientist with strong hands-on experience in Voicebot development, Conversational AI, Machine Learning, NLP, and speech technologies.

The ideal candidate should have practical experience in building end-to-end voice-driven automation systems, including ASR, NLU, dialog management, and TTS pipelines. The role will involve working on AI-powered voicebots, chatbots, and predictive models for finance, banking, and insurance use cases.

Key Responsibilities

• Develop and deploy machine learning, NLP, and speech-based models for BFSI datasets.
• Build end-to-end Voicebots covering ASR, NLU, dialog management, and TTS pipelines.
• Work with speech recognition engines such as OpenAI Whisper, Google Speech-to-Text, Azure Cognitive Speech, and Amazon Transcribe.
• Work with text-to-speech systems such as Google WaveNet, Amazon Polly, and Azure Neural TTS.
• Create and optimize Chatbots using Rasa, Dialogflow, LangChain, HuggingFace Transformers, or LLM-based frameworks.
• Implement entity extraction, intent classification, embeddings, and transformer-based models.
• Perform data preprocessing, feature engineering, model training, optimization, and evaluation.
• Integrate AI/ML models into production environments using REST APIs, Docker, and cloud services.
• Analyze model performance and improve accuracy, latency, and response quality.
• Collaborate with cross-functional teams to design conversational flows, voice UX, and call automation logic.

Required Skills and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
• Strong proficiency in Python, Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with ASR and TTS technologies.
• Experience with OpenAI Whisper, Google Speech-to-Text, Azure Cognitive Speech, Amazon Transcribe, WaveNet, Amazon Polly, or Azure Neural TTS.
• Strong knowledge of NLP, NLU, Conversational AI, and speech-based AI systems.
• Experience with frameworks such as Rasa, Dialogflow, LangChain, and HuggingFace Transformers.
• Practical experience in building Voicebots, Chatbots, and conversational flows.
• Familiarity with BFSI datasets and financial services use cases.
• Cloud deployment experience using AWS, Azure, or GCP.
• Ability to communicate technical ideas clearly and work with cross-functional teams.

Preferred / Good to Have Skills

• Knowledge of Twilio Voice, SIP/VoIP systems, or call automation platforms.
• Experience with real-time streaming pipelines for speech processing.
• Exposure to vector databases such as FAISS or Pinecone for RAG-based chatbots.
• Experience with Docker, CI/CD pipelines, REST APIs, and microservices architecture.

Required Experience

• Proven experience in building and deploying Voicebots using ASR + NLU + TTS.
• Practical experience creating Chatbots for customer support or automation.
• Experience in AI implementation within financial services.
• Cloud-based ML deployment exposure using AWS, Azure, or GCP.

Why Join Us?

• Opportunity to work on real-world AI, voicebot, chatbot, and automation solutions.
• Exposure to BFSI and enterprise AI use cases.
• Collaborative and innovation-driven work environment.
• Opportunity to build scalable AI solutions from development to deployment.

Interested candidates can apply with their updated resume at singh.jyoti@cognitensor.com , https://forms.gle/TrTUcsYUvur86yGZ9