Applied Scientist

{
  "content_hash": "1826ef756e887021862039206dd2d0a14827f1f83f9e6746434371f84b0f9d0e",
  "source_hash": "360c2ce5d8757069189c0f8ab07adf1ea79dcb3129a4d79b1415e84a32b4b296",
  "last_changed_at": "2026-05-31T17:51:10.462Z",
  "active_status": "active"
}

{
  "dedupe": null,
  "language": "en",
  "location": {
    "raw": "New York, New York, NY, United States",
    "city": "New York",
    "region": "NY",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.8
  },
  "salary_max": null,
  "salary_min": null,
  "inferred_at": "2026-06-20T10:19:32.735Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "New York, New York, NY, United States",
      "city": "New York",
      "region": "NY",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.8
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": null,
  "salary_period": null,
  "workplace_type": null,
  "salary_currency": null
}

{}

{
  "Id": "e52bff03-fbf2-49f2-b678-817cb8eeb514",
  "Title": "Applied Scientist",
  "Distance": null,
  "Featured": true,
  "FullTime": true,
  "Locations": [
    {
      "Id": "72046df5-3ac6-50a7-95dd-d7fc8d1ffb91",
      "Address": {
        "City": "New York",
        "Line1": "1 Penn Plz",
        "Line2": "Suite 2105",
        "State": {
          "Code": "NY",
          "Name": "New York"
        },
        "Country": {
          "Code": "USA",
          "Name": "United States"
        },
        "PostalCode": "10119"
      },
      "Coordinates": {
        "Latitude": 40.750946253888,
        "Longitude": -73.991595447991
      },
      "DisplayName": false,
      "LocalizedName": null,
      "SourceOfTruth": 1,
      "DisplayAddress": true,
      "DisplayLocationId": false,
      "DisplayDescription": false,
      "LocalizedLocationId": null,
      "DisplayStreetAddress": false,
      "LocalizedDescription": "New York"
    }
  ],
  "MatchScore": 1,
  "PostedDate": "2025-10-30T14:29:56.442Z",
  "JobCategoryName": "United States",
  "JobLocationType": 0,
  "OpportunityType": 0,
  "BriefDescription": "•\tPh.D. in Computer Science, Electrical Engineering, or a related field specializing in AI, Machine Learning used in the security domain.\n•\tResearch Excellence: Publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, USENIX, CCS, IEEE).\n•\tTechnical Expertise:\nDeep understanding of modern ML (LLMs, GNNs, RL, anomaly detection).\no\tExperience applying AI to security, threat intelligence, or autonomous systems.\no\tStrong background in AI safety, robustness, or trustworthy ML.\no\tSkilled in Python, PyTorch/TensorFlow, and data frameworks for experimentation and deployment.\n•\tMindset: Curious, rigorous, and impact-driven. You enjoy moving from theory to production and thrive at the intersection of AI and real-world security challenges.",
  "MatchedLocations": [],
  "RequisitionNumber": "APPLI001305"
}