AI Engineer_Audio

Job Title: Research Engineer / Senior Research Engineer – Audio AI
Location: Bangalore, India
Experience: 2 - 5 Years
Joining: Immediate

We are seeking a highly motivated Research Engineer / Senior Research Engineer – Audio AI to join our AI research and product development team. The ideal candidate should have strong hands-on experience in Audio Machine Learning (ML), Deep Learning (DL), Speech Processing, and Audio AI Model Development.

The role involves designing, developing, training, fine-tuning, and optimizing Audio AI models for real-world product applications. The candidate will work on speech and audio technologies including Wake Word Detection, Automatic Speech Recognition (ASR), Voice Activity Detection (VAD), Acoustic Modeling, Audio Denoising, and Noise Analysis while leveraging modern deep learning architectures such as CNNs, RNNs, Transformers, Large Audio Models, and Large Language Models (LLMs).

The candidate should be capable of implementing research papers, developing models from scratch, optimizing model performance, and supporting deployment on product and edge-device environments.

Audio AI Research & Development

• Design, develop, train, and fine-tune Audio ML/DL models based on product requirements.
• Build Audio AI models from scratch for new product use cases.
• Study, implement, and evaluate state-of-the-art research papers.
• Apply transfer learning techniques to improve model performance.
• Optimize models for accuracy, latency, memory utilization, and runtime efficiency.
• Perform model benchmarking, performance validation, and comparative analysis.

Speech & Audio Intelligence

• Develop and optimize solutions for:
  • Wake Word Detection
  • Automatic Speech Recognition (ASR)
  • Voice Activity Detection (VAD)
  • Acoustic Modeling
  • Noise Analysis
  • Audio Denoising
• Analyze audio data characteristics, waveform behavior, and signal quality.
• Develop audio preprocessing and feature extraction pipelines.
• Implement noise augmentation and audio mixing techniques.

Transformer Models & LLMs

• Train, fine-tune, and optimize transformer-based architectures.
• Fine-tune Large Language Models (LLMs) for audio and speech-related applications.
• Improve transformer and LLM performance in terms of:
  • Accuracy
  • Latency
  • Runtime efficiency
  • Resource utilization

Edge AI & Deployment

• Optimize Audio AI models for deployment on edge and embedded devices.
• Support model integration into production environments.
• Work with software and embedded teams to ensure successful deployment.
• Implement model compression and optimization techniques for resource-constrained systems.

Cross-Functional Collaboration

• Work closely with AI researchers, software engineers, embedded teams, and product stakeholders.
• Convert research concepts into scalable product-level solutions.
• Support system integration, troubleshooting, and production validation activities.

Audio AI & Speech Processing

• Strong experience in Audio AI model development and optimization.
• Hands-on experience in Audio Machine Learning and Deep Learning.
• Experience building Audio AI models from scratch.
• Strong understanding of:
  • Audio Preprocessing
  • Audio Feature Extraction
  • Audio Signal Analysis
  • Speech Processing
  • Waveform Analysis
• Experience in:
  • Automatic Speech Recognition (ASR)
  • Voice Activity Detection (VAD)
  • Wake Word Detection
  • Acoustic Modeling
  • Audio Denoising
  • Noise Analysis

Machine Learning & Deep Learning

Strong hands-on experience with:

Frameworks

• PyTorch
• TensorFlow
• Keras

Deep Learning Architectures

• CNN and Variants
• RNN
• LSTM
• GRU
• Attention Mechanisms
• Transformers
• Large Audio Models

Large Audio Models

Hands-on experience with:

• wav2vec
• Whisper
• Other modern speech/audio foundation models

Signal Processing

Strong fundamentals in:

• Digital Signal Processing (DSP)
• Audio Signal Processing
• Time-Domain Analysis
• Frequency-Domain Analysis
• Spectral Processing
• Audio Feature Engineering
• Noise Analysis & Denoising