Deep Learning Audio Codec Engineer

Int9 Solutions

4 - 8 years

16 - 25 Lacs

hyderabad bengaluru delhi / ncr

Posted:4 days ago| Platform:

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Skills Required

audio/speech codecs model deployment onnx hardware acceleration deep learning c/c++ pytorch nnapi embedded systems computer architecture model optimization tensorflow python matlab

Work Mode

Work from Office

Job Type

Full Time

Job Description

About the Role:

We are seeking a Deep Audio Coding Optimization and Deployment Engineer to design, implement, and optimize deep learning models for audio coding. This role focuses on improving model efficiency, deploying models to real-world environments, and collaborating with cross-functional teams to advance audio coding technology.

Key Responsibilities:

Develop and implement algorithms for efficient training and real-time inference of deep audio coding models
Optimize models for accuracy, speed, size, and computational efficiency, including model compression techniques (quantization, pruning, distillation)
Deploy AI models as reference code for standards and ensure performance on mobile and embedded architectures
Profile, test, and optimize models using hardware acceleration where applicable
Collaborate with product managers, engineers, and researchers to define and refine model evaluation methods
Research and implement the latest machine learning and inference technologies to enhance audio coding solutions

Required Qualifications & Skills:

Masters or PhD in Electrical Engineering, Computer Science, or a related field with a focus on deep learning
Strong experience in audio/speech codecs and digital signal processing
Hands-on experience with deep learning frameworks: PyTorch, TensorFlow, ONNX, NNAPI
Proven experience in model optimization for constrained environments (quantization, pruning, distillation)
Programming proficiency in Python, C/C++, or Matlab
Experience with embedded systems, computer architecture, or high-performance computing
Strong analytical, problem-solving, and team collaboration skills
Preferred Qualifications: Experience with hardware-accelerated inference
Familiarity with standards-based audio coding projects
Prior contributions to open-source audio or ML libraries

Location - Bengaluru,Hyderabad,Delhi / NCR , Chennai , Pune , Kolkata , Ahmedabad , Mumbai

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