About the Job:
We are looking for an experienced Head of AI to lead the development of next-generation voice AI solutions for healthcare. In this role, you will build and optimize production-grade machine learning systems that power real-time voice conversations between patients and clinicians. You will work at the forefront of speech AI, large language models (LLMs), and multimodal AI to create intelligent, clinically aware voice agents that improve patient outcomes and streamline healthcare workflows. This is an opportunity to shape the AI strategy and develop proprietary technology that will serve as a long-term competitive advantage.
Location: Bengaluru, Karnataka (On-site)
Key Responsibilities:
- Design and implement evaluation frameworks to measure, monitor, and continuously improve the performance of AI-powered voice agents.
- Train, fine-tune, and optimize large language models (LLMs), transformer models, and speech models using domain-specific healthcare data.
- Build scalable ML pipelines for data preparation, experimentation, model training, deployment, monitoring, and retraining in production environments.
- Enhance automatic speech recognition (ASR) and text-to-speech (TTS) systems by adapting models for Indian English accents, clinical terminology, and conversational healthcare use cases.
- Collaborate closely with engineering and product leadership to determine when to leverage third-party AI solutions versus developing proprietary models.
- Stay current with advancements in Voice AI, multimodal AI, reinforcement learning, and synthetic data generation to drive innovation and long-term product differentiation.
Qualifications & Skills:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field from premier institutes.
- 5+ years of specialized experience in Machine Learning, with a strong focus on training, fine-tuning, and deploying transformer-based and LLM models.
- Hands-on experience building production-grade ML systems, including model evaluation, monitoring, MLOps, and continuous retraining pipelines.
- Strong expertise in speech technologies, including Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and Voice AI model optimization.
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow, along with experience working with large-scale datasets and ML infrastructure.
- Strong understanding of modern AI research, including multimodal models, reinforcement learning from human feedback (RLHF), synthetic data generation, and production AI best practices.
