AI Engineer_Audio

Job Description

• *Job Description (JD) – Research Engineer / Senior Research Engineer, Audio AI**

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• *Position Details**
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• *Job Title:** Research Engineer / Senior Research Engineer – Audio AI

• *Location:** Bangalore, India

• *Experience:** 2 \- 5 Years

• *Joining:** Immediate

• *Job Summary**
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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.

• *Key Responsibilities**
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### **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.

• *Required Technical Skills**
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### **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