Lead AI Engineer

We are looking for a hands-on Lead AI Engineer to build and optimise Speech AI and Clinical AI solutions. The ideal candidate should have deep expertise in fine-tuning LLMs and ASR models, model evaluation, distributed training, and deploying production-grade AI systems.
Responsibilities:
Fine-tune Speech AI (ASR) and LLM models for clinical applications.
Build training datasets and evaluation pipelines.
Optimise models for latency, scalability, and production deployment.
Lead technical decisions, mentor engineers, and collaborate with Product, Clinical, and MLOps teams.
Design robust AI systems using fine-tuning, RAG, and distributed training techniques.
Required Tech Stack:
Programming: Python, SQL, Bash.
ML Frameworks: PyTorch, Hugging Face (Transformers, PEFT, TRL, Accelerate).
LLMs: Llama, Qwen, Mistral, Gemma.
Fine-Tuning: LoRA, QLoRA, SFT, RLHF, DPO, ORPO, PPO.
Speech AI: Whisper, wav2vec2 HuBERT, Conformer, NeMo, ESPnet, SpeechBrain.
RAG and NLP: RAG, Vector Databases, Prompt Engineering, Clinical NLP.
Distributed Training: DeepSpeed, PyTorch FSDP, Multi-GPU.
Inference: ONNX, TensorRT, vLLM, Triton Inference Server.
Cloud and MLOps: AWS/GCP/Azure, Docker, Kubernetes, MLflow/W& B, Git, CI/CD.

Experience
6-10 yrs