Job Title: AI/ML Engineer (Voice Chat Process)

Job Summary:

We are looking for a skilled AI/ML Engineer with expertise in voice chat processing to join our innovative team. The ideal candidate will have a strong background in machine learning, natural language processing (NLP), and speech recognition technologies to develop and optimize voice-enabled AI solutions. This role involves working with speech-to-text (STT), text-to-speech (TTS), conversational AI models, and real-time voice processing.

Key Responsibilities:

• Design, develop, and deploy AI/ML models for voice chat applications.
• Work on speech recognition, text-to-speech, and natural language processing (NLP) technologies.
• Train and fine-tune ASR (Automatic Speech Recognition) models for improved accuracy.
• Optimize real-time speech processing pipelines.
• Implement dialog management for conversational AI.
• Integrate AI-driven voice systems with existing platforms and applications.
• Conduct model evaluations and improve accuracy using data annotation and labeling techniques.
• Collaborate with software developers, data scientists, and UX/UI teams to enhance voice-enabled interfaces.
• Stay up to date with the latest AI research, frameworks, and tools in the voice processing domain.

Required Skills & Qualifications:

• Bachelor’s/Master’s/PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
• Strong programming skills in Python, TensorFlow, PyTorch, or other AI/ML frameworks.
• Experience with speech-to-text (STT) and text-to-speech (TTS) technologies (e.g., Google Speech API, Microsoft Azure Speech, IBM Watson, Kaldi, Mozilla DeepSpeech).
• Hands-on experience with NLP models, including BERT, GPT, or similar architectures.
• Knowledge of voice-based chatbot development (e.g., Dialogflow, Rasa, Amazon Lex, or custom solutions).
• Experience in real-time audio processing and speech enhancement.
• Familiarity with cloud platforms (AWS, GCP, Azure) and deployment strategies.
• Strong understanding of deep learning techniques for speech processing.
• Proficiency in data preprocessing, feature engineering, and model evaluation.
• Ability to work with large datasets and optimize ML models for performance.

Preferred Qualifications:

• Experience with multilingual speech recognition and adaptation.
• Knowledge of edge computing and embedded AI for voice applications.
• Understanding of privacy and security aspects in voice AI applications.
• Experience with reinforcement learning for conversational AI.