AI/ML Engineer

Job Title: AI / ML Engineer with GraphDB / Knowledge Graph / Neo4j / Entity resolution. Location: Dallas, TX (Hybrid) Duration: Long Term contract Job Description: Client is looking for candidates who have experience in building: • Ontology from large scale data (requires experience in entity resolution, probabilistic pattern matching) • Agentic knowledge-based enrichment (automated data gap identification, and data enrichment) • Anomaly detection on top of knowledge graph data at scale • Fine tuning pipeline (including dataset generation, tuning, evaluation, deployment) for small language models and reasoning models • Good depth in building models on top of unstructured data About the Role: • Clients is seeking a Sr Data and Gen AI Engineer with strong expertise in knowledge graph, Graph DB, Vector DB, Neo4j, RAG, and similar technologies. • This engineer will design and implement data infrastructure that enables efficient fine-tuning and deployment of large language models (LLMs) on client servers for low-latency inference. • The role demands a hands-on technologist who can architect, build, and optimize data systems serving enterprise-grade AI use cases. Key Responsibilities: • Design and implement GraphDB and VectorDB solutions to store, query, and retrieve structured and unstructured financial data. • Build knowledge graph pipelines integrating multiple data sources to support LLM fine-tuning and retrieval-augmented generation workflows. • Set up scalable data pipelines for model training, embedding generation, and data preprocessing • Collaborate with AI researchers and ML engineers to prepare data and infrastructure for fine-tuning open-source or proprietary LLMs. • Deploy and optimize model hosting for fast inference on on-prem or cloud GPU servers. • Ensure data governance, lineage and compliance with internal and regulatory standards. Looking forward for your reply.