Voice Recognition Engineer Specialist

1 day ago

Chennai, Tamil Nadu, India Kaizen Voiz Full time

Company Overview

Kaizen Voiz is a leading innovator in voice-driven solutions, dedicated to empowering individuals through cutting-edge speech recognition technology.

Estimated Salary: $120,000 - $180,000 per year

Job Description

We are seeking a highly skilled Voice Recognition Engineer Specialist to join our team. The ideal candidate will be at the forefront of developing and deploying advanced speech recognition systems integrated with NLP, NLU, Generative AI, and LLMs to create innovative voice-driven solutions for various industries.

Key Responsibilities:

  • ASR Development: Design and optimize state-of-the-art Automatic Speech Recognition (ASR) systems using frameworks like Kaldi, Whisper, NeMo, or wav2vec, ensuring high accuracy and efficiency.
  • Language Models: Fine-tune and deploy Large Language Models (LLMs) such as Open AI's GPT, BERT, or T5 for speech-to-text and text generation applications, leveraging their potential for improved results.
  • NLP/NLU Integration: Develop pipelines for understanding natural language inputs, enhancing accuracy for tasks like intent recognition, entity extraction, and sentiment analysis, driving business decisions.
  • Generative AI Applications: Implement Generative AI techniques for conversational AI systems, voice assistants, and real-time transcription services, pushing the boundaries of human-machine interaction.
  • End-to-End Pipelines: Build and optimize scalable and real-time speech-to-text pipelines using tools like TensorFlow, PyTorch, or ONNX, ensuring seamless integration with existing infrastructure.
  • Acoustic Modeling: Work on advanced acoustic modeling techniques, including self-supervised learning for low-resource languages, expanding the reach of our speech recognition solutions.
  • Cross-Functional Collaboration: Collaborate with data scientists, linguists, and product teams to deliver high-quality, user-centric solutions that meet business needs and exceed expectations.
  • Performance Tuning: Continuously enhance system accuracy and latency while maintaining privacy and robustness, guaranteeing a secure and reliable experience for users.
  • Cloud Deployment: Deploy speech recognition systems on cloud platforms like AWS, Azure, or Google Cloud using services such as AWS Transcribe or Azure Cognitive Services, ensuring scalability and flexibility.

Required Skills:

  • Programming Expertise: Strong programming skills in Python, C++, or Java, with experience in ML/DL frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Hands-on Experience: Hands-on experience with ASR tools like Kaldi, Whisper, or wav2vec 2.0, and proficiency in NLP/NLU frameworks: Hugging Face Transformers, SpaCy, or NLTK.
  • Generative AI Technologies: Familiarity with Generative AI technologies and tools like LangChain, Haystack, or Prompt Engineering for LLMs, driving innovation in conversational AI.
  • Signal Processing: Strong knowledge of signal processing, acoustic features, and feature extraction techniques (e.g., MFCC, PLP, spectrograms), ensuring accurate speech recognition.
  • Real-Time Streaming: Understanding of real-time streaming technologies and APIs (e.g., Flask, WebSockets), enabling seamless integration with existing systems.

Preferred Qualifications:

  • Advanced Degree: MS or PhD in Computer Science, AI, ML, or related fields, demonstrating expertise in speech recognition and related areas.
  • Low-Resource Languages: Experience working on low-resource language ASR systems, expanding the reach of our speech recognition solutions.
  • Privacy-Preserving AI: Familiarity with privacy-preserving AI techniques, ensuring the security and reliability of our speech recognition systems.
  • Production-Ready Models: Proven track record of deploying production-ready models in cloud environments, driving business success.

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