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Plus 2via Lever
Machine Learning Engineer Intern
Santa Clara, CAPosted 6d ago
ML EngineerEntry LevelFull-time
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About the Role
PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.
We’re seeking an enthusiastic and driven Simulation/ML Engineer Intern to join our team. In this role, you’ll help build an internal AI assistant that lets employees instantly access company knowledge through natural-language questions. Built on an open-source large language model (like Qwen) and fine-tuned with Plus’s internal documents, test results, and Slack data, it uses retrieval-augmented generation (RAG) to deliver accurate answers securely within our environment. One use case is allow user to ask general questions about test performance through a chat window, and the system will retrieve related test results from bagdb, pluscene (simulation), and the WIP right-seater database (road test), and generate natural language responses to answer questions regarding to things like passing rate, test mileages, coverage weak points, suggested test type, etc.
We’re seeking an enthusiastic and driven Simulation/ML Engineer Intern to join our team. In this role, you’ll help build an internal AI assistant that lets employees instantly access company knowledge through natural-language questions. Built on an open-source large language model (like Qwen) and fine-tuned with Plus’s internal documents, test results, and Slack data, it uses retrieval-augmented generation (RAG) to deliver accurate answers securely within our environment. One use case is allow user to ask general questions about test performance through a chat window, and the system will retrieve related test results from bagdb, pluscene (simulation), and the WIP right-seater database (road test), and generate natural language responses to answer questions regarding to things like passing rate, test mileages, coverage weak points, suggested test type, etc.
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