Machine Learning Engineer Intern

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  "last_changed_at": "2026-05-29T06:58:18.050Z",
  "active_status": "active"
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  "language": "en",
  "location": {
    "raw": "Santa Clara, CA",
    "city": "Santa Clara",
    "region": "CA",
    "country": "United States",
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    "language": "en",
    "location": {
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      "city": "Santa Clara",
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  "salary_period": "hour",
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{
  "lists": [
    {
      "text": "Responsibilities:",
      "content": "\n<li><span data-sheets-root=\"1\">Build an AI Assistant: Develop and deploy an internal AI chatbot that allows employees to query company knowledge and test results using natural language.</span></li>\n<li><span data-sheets-root=\"1\">Implement RAG Architecture: Design and build a secure Retrieval-Augmented Generation (RAG) pipeline to pull contextual data from internal sources without compromising data privacy.</span></li>\n<li><span data-sheets-root=\"1\">Develop Data Pipelines: Create automated pipelines to ingest, clean, and structure data from diverse sources, including internal documents, Slack conversations, and autonomous driving databases (bagdb, pluscene, and right-seater logs).</span></li>\n<li><span data-sheets-root=\"1\">Fine-Tune Open-Source LLMs: Work with open-source models (such as Qwen) and fine-tune them to accurately understand and process company-specific terminology and AV testing metrics.</span></li>\n<li><span data-sheets-root=\"1\">Generate Actionable Insights: Enable the system to synthesize complex data across simulation and road tests to answer questions about passing rates, test mileages, coverage gaps, and testing recommendations.</span></li>\n"
    },
    {
      "text": "Required Skills:",
      "content": "\n<li><span data-sheets-root=\"1\">Machine Learning &amp; NLP: Solid understanding of Large Language Models (LLMs), natural language processing, and prompt engineering.</span></li>\n<li><span data-sheets-root=\"1\">Python Programming: Strong proficiency in Python for machine learning workflows, scripting, and backend system integration.</span></li>\n<li><span data-sheets-root=\"1\">Data Engineering Fundamentals: Experience building data extraction, transformation, and loading (ETL) pipelines, as well as handling both structured and unstructured data.</span></li>\n<li><span data-sheets-root=\"1\">Familiarity with RAG: Core understanding of Retrieval-Augmented Generation workflows, text chunking, and vector embeddings.</span></li>\n"
    },
    {
      "text": "Preferred Skills:",
      "content": "\n<li><span data-sheets-root=\"1\">Open-Source LLM Experience: Hands-on experience deploying, fine-tuning, or quantizing open-source models (e.g., Qwen, LLaMA, Mistral) using frameworks like Hugging Face or vLLM.</span></li>\n<li><span data-sheets-root=\"1\">Vector &amp; Relational Databases: Experience working with vector databases (e.g., Milvus, Chroma, FAISS) as well as querying traditional SQL/NoSQL databases.</span></li>\n<li><span data-sheets-root=\"1\">Autonomous Vehicle Domain Knowledge: Familiarity with autonomous driving data formats (e.g., ROS bags), simulation environments, or road testing metrics.</span></li>\n<li><span data-sheets-root=\"1\">Chatbot Frameworks: Experience with LLM orchestration frameworks such as LangChain or LlamaIndex.</span></li>\n<li><span data-sheets-root=\"1\">Data Security &amp; Privacy: An understanding of best practices for deploying ML models locally or within secure, internally-hosted environments.</span></li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1778811243769,
  "updatedAt": null,
  "categories": {
    "team": "Data",
    "location": "Santa Clara, CA",
    "commitment": "Intern",
    "department": "US Internships",
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      "Santa Clara, CA"
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