Audio Specialist (Remote)

Hired; India; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Hired is seeking an Audio Expert to develop and optimize audio processing models for speech recognition and sound analysis. You will design and refine algorithms to enhance speech clarity in real-world environments, and collaborate with cross-functional teams to deploy scalable audio solutions.

The role requires hands-on work with Python and audio libraries, and experience with ML frameworks and cloud platforms.

Qualifications

• Proficiency in Python and experience with audio processing libraries such as Librosa, PyAudio, or TensorFlow Audio.
• Hands-on experience with speech recognition frameworks, including Whisper, DeepSpeech, or Kaldi.
• Strong background in signal processing, including filtering, noise reduction, and feature extraction.
• Familiarity with machine learning models for audio classification, transcription, or enhancement.
• Experience working with large-scale audio datasets and cloud-based ML platforms like AWS SageMaker or Google Vertex AI.
• Ability to troubleshoot and debug audio-specific issues in both model training and inference pipelines.
• Strong problem-solving skills with a focus on practical, real-world applications of audio technology.

Responsibilities

• Design, implement, and refine audio processing algorithms to enhance speech clarity and accuracy in real-world environments.
• Collaborate with cross-functional teams to integrate audio models into production systems while ensuring scalability and performance.
• Conduct rigorous testing and validation of audio models using real-world datasets to identify and resolve edge cases.
• Optimize audio processing pipelines for latency and computational efficiency without compromising output quality.
• Document technical specifications, model architectures, and evaluation methodologies for team review and future reference.

Skills

Python

Audio processing

Signal processing

ML for audio

Edge-case testing

Tools

Librosa

PyAudio

TensorFlow Audio

Whisper

DeepSpeech

Kaldi

AWS SageMaker

Google Vertex AI

Job description

We are hiring for one of our clients, seeking an Audio Expert to develop and optimize audio processing models for speech recognition and sound analysis applications.

Key Responsibilities:

• Design, implement, and refine audio processing algorithms to enhance speech clarity and accuracy in real-world environments.
• Collaborate with cross-functional teams to integrate audio models into production systems while ensuring scalability and performance.
• Conduct rigorous testing and validation of audio models using real-world datasets to identify and resolve edge cases.
• Optimize audio processing pipelines for latency and computational efficiency without compromising output quality.
• Document technical specifications, model architectures, and evaluation methodologies for team review and future reference.

Required Skills & Qualifications:

• Proficiency in Python and experience with audio processing libraries such as Librosa, PyAudio, or TensorFlow Audio.
• Hands-on experience with speech recognition frameworks, including Whisper, DeepSpeech, or Kaldi.
• Strong background in signal processing, including filtering, noise reduction, and feature extraction.
• Familiarity with machine learning models for audio classification, transcription, or enhancement.
• Experience working with large-scale audio datasets and cloud-based ML platforms like AWS SageMaker or Google Vertex AI.
• Ability to troubleshoot and debug audio-specific issues in both model training and inference pipelines.
• Strong problem-solving skills with a focus on practical, real-world applications of audio technology.

More About the Opportunity:

This role offers a unique opportunity to work with a global leader in the Technology, Information and Internet industry, contributing to advancements in automated speech processing and audio intelligence.

Equal Opportunity Employer:

We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.