Machine Learning Engineer / Researcher (Speech AI)

Job Summary

We are seeking a skilled Machine Learning Engineer / Researcher specializing in Speech-to-Text (STT) and Text-to-Speech (TTS) systems. The candidate will design, develop, and optimize state-of-the-art speech models, contribute to research publications or open-source projects, and deploy scalable solutions. This role offers the opportunity to work on cutting-edge AI applications with high impact, including model fine-tuning, experimentation, and evaluation of speech-based ML systems.

Job Roles & Responsibilities

• Design, develop, and deploy Speech-to-Text (STT) and Text-to-Speech (TTS) models.
• Conduct research and experiments to improve accuracy, latency, and robustness of speech models.
• Implement state-of-the-art deep learning architectures (e.g., Transformers, RNNs, Conformer models) for speech processing.
• Fine-tune open-source or proprietary models for domain-specific applications.
• Collaborate with product and engineering teams to integrate ML models into production systems.
• Evaluate model performance using relevant metrics and optimize pipelines for scalability.
• Contribute to research publications, patents, or open-source repositories showcasing your work.
• Mentor junior engineers or researchers on best practices in speech ML and model deployment.

Cultural Expectations

• Strong understanding of signal processing, NLP, and deep learning applied to speech.
• Proven experience building or deploying STT/TTS models in research or production environments.
• Familiarity with Python, PyTorch, TensorFlow, Hugging Face, or related ML frameworks.
• Ability to document experiments, write reproducible code, and communicate technical results clearly.
• Awareness of emerging trends in speech AI, including self-supervised learning, RAG, or multimodal AI.
• Ownership of end-to-end ML pipelines, including training, evaluation, and deployment.
• Willingness to contribute to ESOP-driven growth-oriented environments.

Hiring Process

• Technical assignment tailored for the role.
• Interview with hiring manager to assess technical skills.
• Live coding task to evaluate coding proficiency.
• Technical interview with senior member from the technical team.
• Final interview with Tech Lead/CTO.