Description

Key Skills: Speech Recognition, LLM, LLM Integration / Orchestration, Python

Roles and Responsibilities:

• Fine-tune and deploy LLMs for voice and speech-to-speech experiences used in real-time conversations.
• Build and optimize inference pipelines for low-latency, high-accuracy voice agents and multimodal interfaces.
• Convert unstructured, noisy real-world audio/text into clean datasets for training and evaluation.
• Integrate and orchestrate LLM components for production workflows, including fallback and observability.
• Own the end-to-end model lifecycle: research, training, deployment, testing, monitoring, and iteration.

Skills Required:

• 5 - 10 years of relevant experience in AI/ML engineering or research roles.
• Speech recognition experience, including building or deploying STT-style systems for real-world audio.
• LLM fine-tuning and deployment experience for instruction tuning or pretraining workflows.
• LLM integration and orchestration experience for production-grade model pipelines.
• Experience shipping ML models with testing, iteration, and monitoring for reliability in production.

Good to Have:

• Python for model development, data processing, and ML pipeline implementation.

Education: B.Tech / M.Tech (Dual) or B.Tech in Computer Science, Computer Engineering, or Computer Application

Key Skills

Education

Any Graduate