Description

You will design and deliver production-grade Generative AI solutions on Google Cloud Platform, focusing on scalable LLM systems, RAG architectures, and agentic workflows.

This role is on-site.

Responsibilities

• Design and deploy production-ready Generative AI applications and APIs on GCP.
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and unstructured data sources.
• Manage end-to-end MLOps pipelines for training, evaluation, deployment, and monitoring using Vertex AI and Kubeflow.
• Optimize model performance through fine-tuning, prompt engineering, and compression techniques like GPTQ and AWQ.
• Architect scalable, secure GCP infrastructure with a focus on IAM, VPC design, and cost efficiency.

Required Skills

• 5+ years of industry experience in Machine Learning.
• 3+ years of hands-on experience building and deploying Generative AI or LLM-based solutions in production.
• Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Deep experience with Google Cloud Platform, including Vertex AI, BigQuery, Dataflow, and Cloud Run.
• Hands-on experience with LLM frameworks like LangChain, LlamaIndex, or Hugging Face.
• Solid understanding of SQL and unstructured data processing.
• Experience with Docker, Kubernetes (GKE), and CI/CD pipelines.

Preferred Skills

• Experience with multi-agent systems and orchestration tools such as LangGraph or AutoGen.
• Deep understanding of vector databases like Vertex AI Vector Search, Pinecone, or Chroma.

Key Skills

Education

Any Graduate