AI/ML Engineer

Job Title:

AI/ML Engineer Location:

Milpitas, CA (Hybrid - 4 days onsite)

Duration:

6+ Months Job Summary

STAFFXPERT LLC

is seeking an AI/ML Engineer on behalf of our client in Milpitas, CA to join a high-impact engineering team focused on building next-generation Generative AI systems. In this role, you will transform advanced AI architectures into scalable, production-ready systems. You will work closely with senior AI architects to develop the core intelligence layer of an enterprise AI platform, with a strong emphasis on Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and high-performance data systems. Key Responsibilities RAG Pipeline Development Design and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines Extract and process high-quality data from PDFs, wikis, FAQs, and enterprise knowledge sources Develop advanced chunking strategies and metadata enrichment techniques Improve retrieval accuracy and relevance through iterative tuning Vector Database & Search Systems Work with vector databases such as Qdrant, Pinecone, or Weaviate Design hybrid search systems combining keyword and semantic retrieval Implement efficient indexing strategies (e.g., HNSW) and optimize similarity search performance Multi-Agent Systems Build agentic workflows using frameworks such as LangGraph, Agno, or Google ADK Develop tools, state management systems, and inter-agent communication logic Orchestrate multi-agent pipelines for complex business automation use cases Data Engineering for AI Build scalable ETL pipelines for unstructured and semi-structured data Transform raw content into structured, searchable knowledge bases Maintain data quality, versioning, and governance standards Evaluation & Optimization Evaluate system performance using frameworks such as RAGAS or LangSmith Optimize prompts, retrieval pipelines, and orchestration logic Reduce hallucinations and improve response relevance and consistency Deployment & Scaling Containerize applications using Docker Deploy low-latency, production-grade AI services Ensure scalability, reliability, and performance optimization in production environments Technical Requirements Strong proficiency in Python (including Asyncio, FastAPI, and Pydantic) Hands-on experience with agentic AI frameworks (LangGraph, Agno, or Google ADK) Experience with vector databases such as Qdrant, Weaviate, Pinecone, or similar Strong understanding of similarity search, embeddings, and HNSW indexing Experience building RAG systems and working with LLM-based applications Strong background in processing and structuring unstructured data sources Familiarity with production deployment practices for AI systems