Intern, Machine Learning Engineer

Focus on developing agentic AI workflows, including planning, retrieval-augmented reasoning (hybrid RAG), tool-use orchestration, and multi-agent collaboration.
Contribute to model development, including customized Vision-Language Models (VLMs) tailored to agent needs, and build a robust MVP pipeline.
Integrate agents with internal tools and services, such as microservices and search/retrieval systems, to demonstrate practical workflows.
Create a compact benchmarking and evaluation suite to measure task completion, retrieval accuracy, and reasoning robustness.
Prepare a concise technical report with design insights and recommended next steps for production deployment.
Qualifications include pursuing a PhD in CS/ML/AI with at least one term remaining, strong Python and PyTorch skills, and the ability to translate research ideas into working prototypes; location is San Jose, CA with daily onsite work.