Description :

Position : Azure AI Tech Lead

Location : Remote / Noida (NCR)

Notice Period : Immediate to 15 days

Mandatory Skills (Tech Stack) :

Category Tools & Technologies :

- Languages & Frameworks Python, PyTorch, TensorFlow, JAX

- Ecosystems HuggingFace Transformers, Diffusers

- LLM & Agentic Frameworks LangChain, LangGraph, LlamaIndex, Semantic Kernel

- MLOps MLflow, Weights & Biases, Kubeflow

- Generative & Agentic AI RAG (FAISS, Pinecone, Weaviate, Milvus), AutoGen, OpenAI Function APIs

- Model Fine-tuning LoRA, QLoRA, Stable Diffusion, DreamBooth, ControlNet

- Machine Learning & DL XGBoost, LightGBM, CNNs, RNNs, Transformers, GNNs

- Computer Vision YOLO, DETR, CLIP, BLIP, SAM, PaddleOCR

- Optimization & Deployment TensorRT, ONNX Runtime, Docker, Kubernetes, REST/gRPC APIs

- Cloud & Monitoring Azure ML, Azure OpenAI, Azure Cognitive Services, Prometheus, Grafana, ELK Stack

JOB DESCRIPTION :

As the Azure AI Tech Lead, you will serve as the principal technical expert leading the design, development, and deployment of advanced AI and ML solutions on the Microsoft Azure platform. You will guide a team of engineers, establish robust architectures, and drive end-to-end implementation of AI projectstransforming proof-of-concepts into scalable, production-ready systems.

Key Responsibilities :

- Lead architectural design and development of AI/ML solutions using Azure AI, Azure OpenAI, and Cognitive Services.

- Develop and deploy scalable AI systems with best practices in MLOps across the full model lifecycle.

- Mentor and upskill AI/ML engineers through technical reviews, training, and guidance.

- Implement advanced generative AI techniques including LLM fine-tuning, RAG systems, and diffusion models.

- Collaborate cross-functionally to translate business goals into innovative AI solutions.

- Enforce governance, responsible AI practices, and performance optimization standards.

- Stay ahead of trends in LLMs, agentic AI, and applied research to shape next-gen solutions.

Qualifications :

- Bachelors or Masters in Computer Science or related field.

- 3.5 to 7 years of experience delivering end-to-end AI/ML solutions.

- Strong expertise in Azure AI ecosystem and production-grade model deployment.

- Deep technical understanding of ML, DL, Generative AI, and MLOps pipelines.

- Excellent analytical and problem-solving abilities; applied research or open-source contributions preferred.