GCP AI/ML Architect with Vertex AI

GCP AI/ML Architect with Gen AI Rosemead, CA (Remote) Contract – 5 months Detailed JD: Designing and deploying scalable, secure, and reliable LLM-based solution, implement Retrieval-Augmented Generation (RAG), model fine-tuning, and agentic workflows to solve complex business problems. Key Responsibilities • Design, build, and maintain production-grade Generative AI applications and APIs on GCP, focusing on Gemini models, RAG architectures, and vector databases. • Develop automated MLOps pipelines (training, evaluation, monitoring, deployment) using Vertex AI, Kubeflow, Cloud Build, and Terraform. • Implement techniques to enhance AI model performance, including fine-tuning, quantization (e.g., GPTQ, AWQ), and prompt engineering to improve accuracy and reduce latency. • Optimize GCP resources for high-performance computing, ensuring scalability, cost-efficiency, and security (IAM, VPC). • Partner with Data Science, Data Engineering, and Product teams to translate business requirements into technical AI/ML roadmaps. • Ensure compliance with data privacy, security regulations (HIPAA, GDPR, if applicable), and ethical AI standards. Required Qualifications • 5-8+ years of industry experience in Machine Learning, with at least 3+ years of hands-on experience in building and deploying Generative AI models and LLMs in a production environment. • Proven experience with Google Cloud Platform (GCP) and its AI suite (Vertex AI, BigQuery, Dataflow, Cloud Run). • Strong expertise in Python and standard data science libraries (scikit-learn, TensorFlow, PyTorch). • Hands-on experience with framework tooling such as LangChain, LlamaIndex, or Hugging Face. • Strong understanding of SQL and unstructured data management. • Familiarity with Docker, Kubernetes (GKE), and CI/CD tools. Preferred Qualifications • Experience with multi-agent systems and orchestration (e.g., LangGraph, AutoGen). • Deep knowledge of Vector Databases (e.g., Vertex AI Vector Search, Pinecone, Chroma). • Google Cloud Professional Machine Learning Engineer certification. • Demonstrated experience leading team projects and mentoring junior engineers.