Simulation Engineer Intern

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    "raw": "Santa Clara, CA",
    "city": "Santa Clara",
    "region": "CA",
    "country": "United States",
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{
  "lists": [
    {
      "text": "Responsibilities:",
      "content": "\n<li><span data-sheets-root=\"1\">LLM Integration: Leverage Large Language Models (LLMs) to architect and implement a pipeline that automatically generates realistic, highly structured driving scenarios.</span></li>\n<li><span data-sheets-root=\"1\">Translate ODDs to Prompts: Convert complex Operational Design Domains (ODDs) and safety/NHTSA guidelines into effective prompt frameworks and programmatic constraints for the model.</span></li>\n<li><span data-sheets-root=\"1\">Simulation Integration: Interface the LLM-generated scenarios directly with the autonomous vehicle simulation environment to create executable, varied testing grounds.</span></li>\n<li><span data-sheets-root=\"1\">Apply Deontic Logic: Incorporate rule-based constraints (deontic logic) to ensure the generated scenarios strictly adhere to or properly test complex traffic laws, rights-of-way, and safety protocols.</span></li>\n<li><span data-sheets-root=\"1\">Quality Assurance &amp; Iteration: Collaborate with the simulation and machine learning teams to evaluate the realism, diversity, and edge-case coverage of the synthetic scenarios, refining the models as needed.</span></li>\n"
    },
    {
      "text": "Required Skills:",
      "content": "\n<li><span data-sheets-root=\"1\">Generative AI &amp; LLM Experience: Strong understanding of Large Language Models, including prompt engineering, API integration, and structuring LLM outputs (e.g., JSON parsing).</span></li>\n<li><span data-sheets-root=\"1\">Programming Proficiency: Strong, hands-on programming skills in Python for machine learning workflows and scripting.</span></li>\n<li><span data-sheets-root=\"1\">Systems Thinking: Ability to translate abstract, real-world concepts (like traffic rules and driving environments) into structured, programmable data and logic.</span></li>\n<li><span data-sheets-root=\"1\">Problem Solving: A highly analytical mindset with a passion for tackling complex challenges at the intersection of AI and physical-world simulation.</span></li>\n"
    },
    {
      "text": "Preferred Skills:",
      "content": "\n<li><span data-sheets-root=\"1\">Simulation Software: Familiarity with autonomous vehicle simulation platforms (e.g., CARLA, LGSVL, or proprietary AV simulators) and procedural generation.</span></li>\n<li><span data-sheets-root=\"1\">Autonomous Driving Context: Knowledge of autonomous driving concepts, Operational Design Domains (ODDs), ADAS systems, or NHTSA safety guidelines.</span></li>\n<li><span data-sheets-root=\"1\">Formal Logic/Rules Engines: Exposure to formal logic, deontic logic, or building rule-based expert systems.</span></li>\n<li><span data-sheets-root=\"1\">Synthetic Data Generation: Prior experience using generative AI for synthetic data generation, automated testing, or scenario creation.</span></li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1778812100747,
  "updatedAt": null,
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    "team": "Data",
    "location": "Santa Clara, CA",
    "commitment": "Intern",
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