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ASR - AI /ML Engineer

0 years

0 Lacs

india

Posted:2 days ago| Platform: Linkedin logo

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Skills Required

ai ml recognition signal azure collaboration latency design tuning learning personalization processing extraction spectrogram model quantization distillation deployment gcp vertex docker containerization orchestration engineering git versioning testing code reliability monitoring logging evaluation metrics test research kaldi pytorch tensorflow aws python fastapi flask service integration kubernetes optimization communication onnx healthcare accessibility

Work Mode

On-site

Job Type

Full Time

Job Description

JOB TITLE : ASR - AI /ML Engineer


JOB SUMMARY

AI/ML Engineer

real-time, low-latency, speech-driven applications


KEY RESPONSIBILITIES


🔹 ASR & Speech Recognition

  • Design, train, and optimize

    ASR models

    (Whisper, Conformer, Wav2Vec2, SpeechBrain, etc.) with focus on

    speaker adaptation

    and

    impaired speech recognition

    . 
  • Implement

    domain adaptation techniques

    (fine-tuning, transfer learning, LoRA) for accent, dialect, and special-use cases. 
  • Develop and integrate

    speaker recognition & personalization modules

    . 


🔹 Signal Processing & Speech Enhancement

  • Apply

    speech enhancement, noise reduction, and denoising algorithms

    to improve input quality. 
  • Work with feature extraction methods (

    MFCC, PLP, spectrogram analysis

    ) for robust ASR performance. 


🔹 Model Optimization

  • Apply

    quantization, pruning, knowledge distillation, and LoRA

    to achieve low-latency, resource-efficient deployment. 
  • Balance trade-offs between

    accuracy, speed, and scalability

    . 


🔹 Cloud & Deployment

  • Deploy AI/ASR pipelines on

    Azure (AKS, Cognitive Services, Functions)

    and

    GCP (Vertex AI, Cloud Run, BigQuery)

    . 
  • Build

    scalable APIs and services

    for real-time speech processing. 
  • Use

    Docker/Kubernetes

    for containerization and orchestration. 
  • Integrate with

    CI/CD pipelines

    for automated model retraining and updates. 


🔹 Backend & Engineering Practices

  • Collaborate with

    backend engineers

    to integrate ASR modules with production systems. 
  • Build

    RESTful APIs and microservices

    for ASR and speech enhancement tasks. 
  • Follow best practices with

    Git, versioning, unit testing, and code reviews

    . 
  • Ensure system reliability, monitoring, and logging for speech pipelines. 


🔹 Evaluation & Continuous Learning

  • Evaluate models with

    WER, CER, SER, RTF

    metrics and real-world test cases. 
  • Incorporate

    user feedback loops

    for continuous improvement. 
  • Stay updated with latest research in

    ASR, Speech AI, and Cloud AI services

    . 


REQUIRED SKILLS AND QUALIFICATIONS


  • Strong experience with

    ASR frameworks

    (Whisper, Conformer, Wav2Vec2, NeMo, Riva, Coqui STT, Kaldi). 
  • Solid background in

    speech signal processing

    (MFCC, PLP, spectrograms, denoising, echo cancellation). 
  • Hands-on with

    Deep Learning frameworks

    (PyTorch, TensorFlow, SpeechBrain). 
  • Cloud deployment experience:

    Azure AI, GCP Vertex AI, AWS (bonus)

    . 
  • Proficiency in

    Python (FastAPI/Flask/Django)

    for backend service integration. 
  • Strong knowledge of

    Docker, Kubernetes, CI/CD pipelines

    . 
  • Familiarity with

    large-scale speech datasets

    (LibriSpeech, Common Voice, custom corpora). 
  • Experience in

    model optimization (quantization, pruning, LoRA)

    . 
  • Excellent problem-solving, collaboration, and communication skills. 


PREFERRED SKILLS


  • Experience with

    real-time speech streaming APIs

    (WebRTC, gRPC). 
  • Exposure to

    multi-lingual ASR

    and

    speech for low-resource languages

    . 
  • Knowledge of

    Edge deployment

    (ONNX, TensorRT, TFLite). 
  • Familiarity with

    healthcare / accessibility-focused speech solutions

    . 

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