Walk-in || Python Audio LLM Foundation Model Developer

Walk - In Interview* Only Male candidate Python Audio LLM Foundation Model Developer Job Summary: We are looking for a Python Audio LLM Foundation Model Developer with hands-on experience in Speech AI, Audio AI, and Foundation Models. The ideal candidate should have strong Python development skills and practical exposure to ASR/STT models, transformer architectures, and deploying AI solutions in production. Key Responsibilities Design, develop, and deploy AI applications using Python. Build and optimize Automatic Speech Recognition (ASR) and Speech-to-Text (STT) pipelines. Work with audio foundation models such as Whisper, Faster-Whisper, wav2vec 2.0, NeMo, Kaldi, or Vosk. Fine-tune transformer-based models using LoRA and QLoRA. Develop real-time or streaming speech processing pipelines with low latency. Implement speaker diarization, Voice Activity Detection (VAD), speaker recognition, and multilingual speech processing. Integrate LLMs with speech AI applications using embeddings and RAG. Optimize models for GPU deployment using CUDA, quantization, and inference optimization. Build REST APIs using FastAPI and deploy applications using Docker, Kubernetes, and cloud platforms. Collaborate with AI researchers and engineering teams for production deployment. .