AI Engineer_Audio

LG Electronics, Inc.; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

LG Electronics, Inc. seeks a Research Engineer / Senior Research Engineer – Audio AI in Bangalore to advance audio ML/DL models for product deployment. You will design, train, and optimize models covering ASR, wake word, VAD, and denoising, with emphasis on edge-friendly architectures.

The role requires hands-on experience with PyTorch/TensorFlow, Transformers, and large audio models, plus collaboration with software and embedded teams for deployment.

Qualifications

• Experience in Audio ML/DL model development.
• Hands-on experience building Audio AI models from scratch.
• Strong understanding of audio preprocessing and feature extraction.
• Experience with ASR, VAD, wake word detection and acoustic modeling.
• Ability to optimize models for edge deployment.

Responsibilities

• Design, develop, train, and fine-tune Audio ML/DL models.
• Build Audio AI models from scratch for new product use cases.
• Study, implement, and evaluate state-of-the-art research papers.
• Apply transfer learning to improve model performance.
• Optimize models for accuracy, latency, memory, and runtime.
• Develop and optimize audio preprocessing and feature extraction pipelines.
• Train transformer-based architectures and LLMs for audio tasks.
• Collaborate with researchers, software, and embedded teams for deployment.

Skills

Audio ML

Deep Learning

Speech Processing

Model Development

Edge AI

Tools

PyTorch

TensorFlow

CNN Variants

RNN

LSTM

GRU

Attention

Transformers

Large Audio Models

Job description

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

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

Job Summary

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

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.
• 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.
• 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.
• 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

• 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

Strong hands-on experience with:

Frameworks

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

Large Audio Models

Hands-on experience with:

• Whisper
• Other modern speech/audio foundation models