Machine Learning Engineer [Speech]

Join our team of passionate researchers and engineers from CMU, IITs and IIITs specialized in generative AI modeling and deep learning. We work on exciting deep learning speech and language technologies for India/Bharat that power incredibly engaging user experiences. We are looking to hire smart machine learning engineers and applied research scientists to build high-quality speech synthesis and natural/expressive TTS systems.

Responsibilities

• Train speech synthesis networks and evaluate their quality and performance.
• Evaluate and diagnose training procedure of both autoregressive and non-autoregressive speech synthesis models. Evaluate and make architectural decisions driven by product requirements.
• Own both research-driven experiment pipelines as well as in-production model quality and capabilities.
• Be involved with ingestion, preprocess, and cleaning of speech data, ensuring its quality, relevance, and adequacy for training and testing purposes.
• Continuously research and experiment with new approaches, methodologies, and algorithms in speech data processing and analysis, staying up-to-date with the latest advancements in the field.

Requirements

• Master's or higher degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience).
• 3+ Years Experience as a Machine Learning Engineer, Data Scientist, Researcher or a similar role with a focus on implementing and training deep neural networks.
• Strong programming skills, with proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience working with speech data, including audio preprocessing, feature extraction, and signal processing techniques.
• Passion for startups and the ability to thrive in a fast-paced, dynamic environment.

Bonus

• On-the-ground experience with speech synthesis technologies including training of SOTA architectures (both two-stage and end-to-end/).
• Familiarity with large-scale distributed computing frameworks and cloud-based ML platforms (e.g., AWS SageMaker, Google Cloud AI Platform).