We are looking for an Audio/Speech Research Intern with hands-on experience in audio model training, evaluation, and open-source research

. The intern will work closely with our research and engineering teams on speech and audio AI systems, contributing to both experimentation and production-oriented research.

Key Responsibilities

- Train, fine-tune, and evaluate speech/audio ML models across tasks such as ASR, TTS, speech understanding, speaker recognition, and audio classification.

- Design and execute model evaluation frameworks

, benchmarks, and error analysis pipelines.

- Work with large-scale audio datasets, including data preparation, quality analysis, preprocessing, and curation.

- Reproduce and experiment with recent speech/audio research papers and open-source models

.

- Contribute improvements, fixes, datasets, benchmarks, or tooling to open-source audio/speech projects

.





- Analyze model failures and develop methodologies to improve model quality, robustness, and generalization.

- Document experiments, findings, and technical insights for internal research and external contributions.

Preferred Background

- Strong fundamentals in machine learning, deep learning, and audio/speech processing

.

- Hands-on experience with

PyTorch and Python.

- Experience training or fine-tuning models using real-world audio datasets.

- Demonstrated

GitHub/open-source contributions

, research projects, papers, or meaningful technical experiments.

- Robust interest in understanding how speech and audio models work beyond simply using APIs.

📌 ML Intern - Audio (India)
🏢 AmplLab
📍 India