Machine Learning Engineer Intern - Scenario Generation

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{
  "lists": [
    {
      "text": "Responsibilities:",
      "content": "<div>\n\n<li><span data-sheets-root=\"1\">Evaluate existing tools for fidelity and efficiency to determine the best baseline.</span></li>\n<li><span data-sheets-root=\"1\">Ingest and process internal, real-world driving logs to fine-tune the model.</span></li>\n<li><span data-sheets-root=\"1\">Connect the prototype to the data pipeline, allowing it to seamlessly ingest map data and output structured scenarios.</span></li>\n<li><span data-sheets-root=\"1\">Translate the generated scenarios into the standardized formats required by the company’s existing simulation engine.</span></li>\n<li><span data-sheets-root=\"1\">Develop metrics to validate the physical realism, diversity, and kinematic feasibility of the generated scenarios.</span></li>\n<li><span data-sheets-root=\"1\">Use generated scenarios to stress-test the vehicle's on-board modules against rare or safety-critical events.</span></li>\n<li><span data-sheets-root=\"1\">Collaborate closely with ML researchers, simulation engineers, and on-board teams to define what makes a scenario useful for their specific needs.</span></li>\n\n</div>"
    },
    {
      "text": "Required Skills:",
      "content": "<div>\n\n<li><span data-sheets-root=\"1\">Solid Python programming skills</span></li>\n<li><span data-sheets-root=\"1\">Familiarity with deep learning frameworks (PyTorch preferred)</span></li>\n<li><span data-sheets-root=\"1\">Basic understanding of generative models (e.g., VAEs, GANs, diffusion models)</span></li>\n<li><span data-sheets-root=\"1\">Experience working with datasets (loading, preprocessing)</span></li>\n\n</div>"
    },
    {
      "text": "Preferred Skills:",
      "content": "<div>\n\n<li><span data-sheets-root=\"1\">Prior exposure to diffusion models</span></li>\n<li><span data-sheets-root=\"1\">Experience with autonomous driving datasets</span></li>\n<li><span data-sheets-root=\"1\">Familiarity with 2D/3D coordinate systems, trajectories, and map representations</span></li>\n<li><span data-sheets-root=\"1\">Experience with experiment tracking and ML tooling</span></li>\n<li><span data-sheets-root=\"1\">Basic understanding of scenario-based testing for autonomous driving systems</span></li>\n\n</div>"
    }
  ],
  "country": "US",
  "createdAt": 1779313808004,
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    "team": "Simulation",
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