Vectara
Data AI · RAG / enterprise search
Vectara currently has 3 active AI-related roles in our index. The most common open titles are: Machine Learning (ML) Engineer, Senior Machine Learning Engineer, Senior/Staff Software Engineer - Pakistan. Most positions are in Engineering.
Vectara's active AI hiring is concentrated in: agents (67%), serving infrastructure (33%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Job postings at Vectara most frequently reference: rag, agent orchestration, multimodal, fine tuning, evals.
Data AI · RAG / enterprise search
Currently tracking 3 active AI roles, up 500% versus the prior 4 weeks. Primary focus: Agent · Engineering.
| Title | Stage | AI score |
|---|---|---|
| Senior Machine Learning Engineer Senior Machine Learning Engineer at Vectara, focusing on building and improving Enterprise AI Agents and RAG platforms. The role involves training, evaluating, and deploying ML models in NLP, Information Retrieval, AI Agents, and Multimodal LLMs, with an emphasis on agentic behavior, hallucination reduction, and orchestration. The company provides a scalable platform for AI Agents and Assistants with a focus on accuracy, security, and explainability. | AgentPost-train | 9 |
| Machine Learning (ML) Engineer Vectara is seeking an ML Engineer to design, prototype, research, and build AI systems for their enterprise RAG platform. The role involves training, evaluating, and deploying ML models in NLP, Information Retrieval, AI Agents, and LLMs, with a focus on improving agent quality, multilinguality, self-supervised learning, agentic behavior, and hallucination reduction. The ideal candidate has 5+ years of experience applying ML to real-world problems, strong Python skills, and domain knowledge in RAG, LLM, information retrieval, or Multimodal LLMs. | AgentData | 9 |
| Senior/Staff Software Engineer - Pakistan Senior/Staff Software Engineer role focused on developing and managing the core infrastructure for an enterprise RAG and Agentic AI platform. Responsibilities include infrastructure automation, CI/CD, deploying and optimizing ML/NLP workloads (especially model inference), and supporting customer deployments. The role requires strong backend development, DevOps, and containerization skills, with experience in ML platforms and observability tools. | ServeAgent | 7 |