Description

You will design and deploy scalable, secure LLM-based solutions on Google Cloud Platform, focusing on Gemini models, RAG architectures, and vector databases.

Responsibilities

• Build and maintain production-grade Generative AI applications and APIs using GCP services.
• Develop automated MLOps pipelines for training, evaluation, monitoring, and deployment using Vertex AI, Kubeflow, Cloud Build, and Terraform.
• Implement model optimization techniques including fine-tuning, quantization (GPTQ, AWQ), and prompt engineering to reduce latency and improve accuracy.
• Partner with Data Science and Product teams to translate business requirements into technical AI/ML roadmaps.
• Ensure compliance with data privacy, security regulations, and ethical AI standards.

Required Skills

• 5-8+ years of industry experience in Machine Learning.
• 3+ years of hands-on experience building and deploying Generative AI models and LLMs in production.
• Strong expertise in Python and data science libraries including scikit-learn, TensorFlow, and PyTorch.
• Proven experience with Google Cloud Platform (GCP) AI suite: Vertex AI, BigQuery, Dataflow, and Cloud Run.
• Hands-on experience with LangChain, LlamaIndex, or Hugging Face.
• Strong understanding of SQL and unstructured data management.
• Familiarity with Docker, Kubernetes (GKE), and CI/CD tools.

Preferred Skills

• Experience with multi-agent systems and orchestration (LangGraph, AutoGen).
• Deep knowledge of Vector Databases (Vertex AI Vector Search, Pinecone, Chroma).

Key Skills

Education

Any Graduate