We are looking for a Conversational Intelligence Engineer with expertise in traditional speech processing, audio analysis, and classical NLP techniques.

The ideal candidate will have a strong foundation in automatic speech recognition (ASR), signal processing, and conversational AI using classical ML approaches.

You will work on designing, implementing, and optimizing speech-to-text pipelines and conversational intelligence systems for various applications.

Key Responsibilities :

- Develop and optimize speech-to-text models using classical ASR techniques.

- Implement signal processing methods for noise reduction and speech enhancement.

- Utilize rulebased NLP and statistical models for conversational AI applications.

- Design feature extraction techniques for improving speech recognition accuracy.

- Work with phonetic models, acoustic modeling, and language modeling for ASR.

- Implement speaker diarization and speech segmentation techniques.

- Collaborate with data engineers to build scalable speech processing pipelines.

- Conduct error analysis and improve transcription accuracy through iterative refinements.

- Stay updated with advancements in traditional speech processing and conversational AI techniques.

Required Qualifications :

- Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related field.

- 3+ years of experience in speech processing and conversational AI.

- Strong proficiency in Python and ML libraries (Kaldi, CMU Sphinx, HTK, OpenAI Whisper).

- Expertise in signal processing, speech feature extraction, and phonetic modeling.

- Experience with SQL and database management for handling extracted speech data.

- Knowledge of probabilistic models, optimization techniques, and statistical inference.

- Familiarity with cloud-based speech processing (AWS Transcribe, Azure Speech Services).

- Strong analytical and problem-solving skills.

Preferred Qualifications :