{
  "schemaVersion": 1,
  "snapshotId": "physical-ai-2026-11-02-6b48026839dc",
  "collectedAt": "2026-11-02",
  "reviewedAt": "2026-11-09",
  "aggregatePath": "/research/physical-ai-careers-2026-11-02.json",
  "aggregateSha256": "65a83512b9998d7d17a0cd1be5aaad273dc57eed13fab66180bd7c81877467e7",
  "rawArchive": {
    "relativeRoot": "research/physical-ai/2026-11-02",
    "normalizedRecords": "postings.jsonl",
    "manifestHash": "6b48026839dcafc9d68144cf3fbedf38889984ad96f667a21e058b4d25f26f14"
  },
  "interpretation": "Contextual guide review layer; original dated research remains unchanged.",
  "roles": {
    "machine-learning-infrastructure-engineer": {
      "recordIds": [
        "agility:greenhouse:6148969004",
        "apptronik:greenhouse:6176116004",
        "physical-intelligence:ashby:1f6cf3eb-f70f-480b-9fff-befd56c7fd07",
        "nuro:greenhouse:7351066",
        "applied-intuition:ashby:091ed808-95c9-420b-8061-0ff2eb9342bc",
        "nimble:greenhouse:4373712009",
        "rhoda:ashby:643d697d-45c4-4505-8967-433df7873134",
        "skydio:ashby:b6be08f7-89c0-48dd-b427-f587f23dbf34",
        "zoox:lever:91ff6263-49fb-421e-860f-36e7b9bae784",
        "zoox:lever:bc11276c-8db7-426e-9d00-d41c2097723a",
        "zoox:lever:2ae1f38f-1b7e-4ec1-8a20-cc3816f96878",
        "zoox:lever:2ed8a665-cee8-4d70-bcb1-e96b6214b371"
      ],
      "auditPath": "research/career-guides/machine-learning-infrastructure-engineer/evidence-audit.json",
      "compensation": [
        {
          "employer": "Nimble Robotics",
          "title": "Senior/Staff Software Engineer, Infrastructure (ML)",
          "url": "https://job-boards.greenhouse.io/nimblerobotics/jobs/4373712009",
          "minimum": 210000,
          "maximum": 300000,
          "currency": "USD",
          "period": "year",
          "basis": "advertised annual salary; base pay where expressly stated",
          "recordId": "nimble:greenhouse:4373712009",
          "location": "San Francisco, CA"
        },
        {
          "employer": "Rhoda AI",
          "title": "Research Member of Technical Staff- Training Systems",
          "url": "https://jobs.ashbyhq.com/rhoda-ai/643d697d-45c4-4505-8967-433df7873134",
          "minimum": 200000,
          "maximum": 300000,
          "currency": "USD",
          "period": "year",
          "basis": "advertised-salary",
          "recordId": "rhoda:ashby:643d697d-45c4-4505-8967-433df7873134",
          "location": "Mountain View, CA"
        },
        {
          "employer": "Skydio",
          "title": "Autonomy Engineer - ML & DL Infrastructure",
          "url": "https://jobs.ashbyhq.com/skydio/b6be08f7-89c0-48dd-b427-f587f23dbf34",
          "minimum": 170000,
          "maximum": 277500,
          "currency": "USD",
          "period": "year",
          "basis": "advertised annual salary; base pay where expressly stated",
          "recordId": "skydio:ashby:b6be08f7-89c0-48dd-b427-f587f23dbf34",
          "location": "San Mateo, CA"
        }
      ],
      "skillPresentation": "qualitative-source-comparison",
      "scopeNote": "Broad cohort includes external model APIs, data-system specializations and a multi-team graduate opening. Do not treat raw counts as clean vacancies or skill prevalence."
    }
  },
  "records": [
    {
      "id": "agility:greenhouse:6148969004",
      "employerId": "agility",
      "employer": "Agility Robotics",
      "title": "Senior Software Engineer, AI/ML Platform",
      "locations": [
        "Remote",
        "Remote, Oregon, United States"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://www.agilityrobotics.com/about/job-post?gh_jid=6148969004",
      "verifiedAt": "2026-11-02T17:46:56+00:00",
      "sourceTextSha256": "d7f3829ce2350282d2014b771e963761ff61e99398ff4938611d7cd4aa3afd22",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/agility.json",
      "rawSourceFileSha256": "ac356350940b45d164fbf75881d9254f4c3aadaa5e83e8f798a621610cb7c731",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Humanoid ML platform, orchestration, experiment tracking, model management and deployment lifecycle.",
      "qualification": "5+ years of software engineering experience, with at least 2+ years working on ML infrastructure, data platforms or MLOps systems in production environments.",
      "qualificationSpans": [
        {
          "text": "5+ years of software engineering experience, with at least 2+ years working on ML infrastructure, data platforms or MLOps systems in production environments.",
          "start": 2839,
          "end": 2996
        }
      ]
    },
    {
      "id": "apptronik:greenhouse:6176116004",
      "employerId": "apptronik",
      "employer": "Apptronik",
      "title": "Senior Software Engineer, ML Infrastructure",
      "locations": [
        "Austin, TX"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://boards.greenhouse.io/apptronik/jobs/6176116004?gh_jid=6176116004",
      "verifiedAt": "2026-11-02T17:46:56+00:00",
      "sourceTextSha256": "654acc00f60725cdb74838f3f44541986f44bfacd061a386363c3b31c16c4718",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/apptronik.json",
      "rawSourceFileSha256": "a43b6624a9466a3a5cfa614e697d2e48d3ad0436d985bc8c694cce572962529b",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "role-reviewed",
      "scope": "Humanoid data/model platform, reproducible training, simulation evaluation and model qualification.",
      "qualification": "Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field, or equivalent experience.",
      "qualificationSpans": [
        {
          "text": "Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field, or equivalent experience.",
          "start": 5450,
          "end": 5574
        }
      ]
    },
    {
      "id": "physical-intelligence:ashby:1f6cf3eb-f70f-480b-9fff-befd56c7fd07",
      "employerId": "physical-intelligence",
      "employer": "Physical Intelligence",
      "title": "ML Infra Engineer, Data Systems",
      "locations": [
        "San Francisco"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.ashbyhq.com/physicalintelligence/1f6cf3eb-f70f-480b-9fff-befd56c7fd07",
      "verifiedAt": "2026-11-02T17:47:02+00:00",
      "sourceTextSha256": "4e3098dc505ddc6e62f9c36870e333d55e13215baddfe8076af4d95492689109",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/physical-intelligence.json",
      "rawSourceFileSha256": "4636b655b7fab48b151da10f872a9268960654cc165ce7e06a60e83e91cc5c99",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Training-time data access, sharding, caching and distributed storage. Boundary with robotics data engineering.",
      "qualification": "Experience building distributed systems or large-scale data pipelines.",
      "qualificationSpans": [
        {
          "text": "Experience building distributed systems or large-scale data pipelines.",
          "start": 2214,
          "end": 2284
        }
      ]
    },
    {
      "id": "nuro:greenhouse:7351066",
      "employerId": "nuro",
      "employer": "Nuro",
      "title": "Software Engineer, AI Platform - New Grad",
      "locations": [
        "Mountain View, California (HQ)",
        "Nuro HQ - Mountain View, CA"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://nuro.ai/careersitem?gh_jid=7351066",
      "verifiedAt": "2026-11-02T17:46:58+00:00",
      "sourceTextSha256": "0b0059f5db0de773882b9cf9a0c371b3cb7eb08e66cefb9295396ac7dfbc68ae",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/nuro.json",
      "rawSourceFileSha256": "04489048507f4a19cf30d818b4e71d7d1214f0a81a8ea6e18060d7f269628e17",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Broad AI Platform new-graduate opening spanning multiple teams including ML infrastructure; not a dedicated ML infrastructure placement or salary observation.",
      "qualification": "You are a current Bachelor’s Degree or Master’s Degree candidate in Computer Science, Electrical Engineering, Robotics, or related field, graduating before or in June 2027.",
      "qualificationSpans": [
        {
          "text": "You are a current Bachelor’s Degree or Master’s Degree candidate in Computer Science, Electrical Engineering, Robotics, or related field, graduating before or in June 2027.",
          "start": 2988,
          "end": 3160
        }
      ]
    },
    {
      "id": "applied-intuition:ashby:091ed808-95c9-420b-8061-0ff2eb9342bc",
      "employerId": "applied-intuition",
      "employer": "Applied Intuition",
      "title": "Research Engineer - AI/RL Infrastructure",
      "locations": [
        "Sunnyvale"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.ashbyhq.com/applied/091ed808-95c9-420b-8061-0ff2eb9342bc",
      "verifiedAt": "2026-11-02T17:47:01+00:00",
      "sourceTextSha256": "28446b6cb65cc6bd36747494ada8cbdb55e340b5e91b6ec81d9a515d11c2b53f",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/applied-intuition.json",
      "rawSourceFileSha256": "739ece566c65cb625b82dfc9215d9731c2e155e928edea1dd0ea0b5c782c80a9",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Physical-AI research infrastructure, distributed training, evaluation and multimodal data pipelines.",
      "qualification": "Masters or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field",
      "qualificationSpans": [
        {
          "text": "Masters or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field",
          "start": 4743,
          "end": 4862
        }
      ]
    },
    {
      "id": "nimble:greenhouse:4373712009",
      "employerId": "nimble",
      "employer": "Nimble Robotics",
      "title": "Senior/Staff Software Engineer, Infrastructure (ML)",
      "locations": [
        "San Francisco, CA",
        "San Francisco, California, United States"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://job-boards.greenhouse.io/nimblerobotics/jobs/4373712009",
      "verifiedAt": "2026-11-02T17:46:56+00:00",
      "sourceTextSha256": "a919457f7bde092e671ab9e7fb860b49d6170c4654f1905b55e5e1c510fd175e",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/nimble.json",
      "rawSourceFileSha256": "610fe002902c60c563cae3837e754353d30671c4264c8e012a1607609ddef81c",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Robot training/inference infrastructure, GPU performance, reproducibility, scheduling and data ingestion.",
      "qualification": "Bachelor’s, Master’s, or PhD in Computer Science or a related field, or equivalent practical experience.",
      "qualificationSpans": [
        {
          "text": "Bachelor’s, Master’s, or PhD in Computer Science or a related field, or equivalent practical experience.",
          "start": 3718,
          "end": 3822
        }
      ]
    },
    {
      "id": "rhoda:ashby:643d697d-45c4-4505-8967-433df7873134",
      "employerId": "rhoda",
      "employer": "Rhoda AI",
      "title": "Research Member of Technical Staff- Training Systems",
      "locations": [
        "Mountain View"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.ashbyhq.com/rhoda-ai/643d697d-45c4-4505-8967-433df7873134",
      "verifiedAt": "2026-11-02T17:47:01+00:00",
      "sourceTextSha256": "533222417ea35355e89f242c8fb6b608848fb606114fb5cb6a135b16aedc8fa2",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/rhoda.json",
      "rawSourceFileSha256": "57292cd4a63e78bba309cca3f2dd2b54a447c617ae01fb0a2d48033f76eb01bc",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Hands-on multimodal training systems performance, communication, memory and scaling analysis.",
      "qualification": "Proven track record improving large-scale distributed training performance",
      "qualificationSpans": [
        {
          "text": "Proven track record improving large-scale distributed training performance",
          "start": 3146,
          "end": 3220
        }
      ]
    },
    {
      "id": "skydio:ashby:b6be08f7-89c0-48dd-b427-f587f23dbf34",
      "employerId": "skydio",
      "employer": "Skydio",
      "title": "Autonomy Engineer - ML & DL Infrastructure",
      "locations": [
        "San Mateo, California, United States"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.ashbyhq.com/skydio/b6be08f7-89c0-48dd-b427-f587f23dbf34",
      "verifiedAt": "2026-11-02T17:53:31+00:00",
      "sourceTextSha256": "c1307e2fe9777799efe00604372d5c637bf1326bbab004fff03d7d571eba8c89",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/skydio.json",
      "rawSourceFileSha256": "3d1edb2f02e30679b554b5a9864a69c57110567352bc2eb1f63780e818c62304",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Drone ML lifecycle: data workflows, training, model delivery and monitoring.",
      "qualification": "Demonstrated hands-on experience with cloud-based ML platforms, containerization technologies, ML Ops platforms and databases",
      "qualificationSpans": [
        {
          "text": "Demonstrated hands-on experience with cloud-based ML platforms, containerization technologies, ML Ops platforms and databases",
          "start": 2301,
          "end": 2426
        }
      ]
    },
    {
      "id": "zoox:lever:91ff6263-49fb-421e-860f-36e7b9bae784",
      "employerId": "zoox",
      "employer": "Zoox",
      "title": "Software Engineer, ML Training Optimization",
      "locations": [
        "Foster City, CA"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.lever.co/zoox/91ff6263-49fb-421e-860f-36e7b9bae784",
      "verifiedAt": "2026-11-02T17:46:57+00:00",
      "sourceTextSha256": "e579aaedde15947b82d54f5e2c7780c0ed9dceb30298ec7db3f1b4c3391cee18",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/zoox.json",
      "rawSourceFileSha256": "af11da595e335bd51385085b58eab9b3577cecac9926f2eaacec64154893a5b3",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "ML training optimization, distributed execution, profiling and performance benchmarks.",
      "qualification": "4+ years of total experience, including 2+ years working on large-scale model training platforms.",
      "qualificationSpans": [
        {
          "text": "4+ years of total experience, including 2+ years working on large-scale model training platforms.",
          "start": 2564,
          "end": 2661
        }
      ]
    },
    {
      "id": "zoox:lever:bc11276c-8db7-426e-9d00-d41c2097723a",
      "employerId": "zoox",
      "employer": "Zoox",
      "title": "Software Engineer, ML Inference Optimization",
      "locations": [
        "Foster City, CA"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.lever.co/zoox/bc11276c-8db7-426e-9d00-d41c2097723a",
      "verifiedAt": "2026-11-02T17:46:57+00:00",
      "sourceTextSha256": "9ed15fafed0a0c8a0ab75fcc4b3a2a9e14886eff820b2fa5a0d19c0a99cd14f8",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/zoox.json",
      "rawSourceFileSha256": "af11da595e335bd51385085b58eab9b3577cecac9926f2eaacec64154893a5b3",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "ML inference and training performance optimization for autonomous vehicles.",
      "qualification": "4+ years of total experience, including 2+ years of working on large-scale model training or inference platforms.",
      "qualificationSpans": [
        {
          "text": "4+ years of total experience, including 2+ years of working on large-scale model training or inference platforms.",
          "start": 2146,
          "end": 2259
        }
      ]
    },
    {
      "id": "zoox:lever:2ae1f38f-1b7e-4ec1-8a20-cc3816f96878",
      "employerId": "zoox",
      "employer": "Zoox",
      "title": "Senior/Staff Software Engineer, ML Training Optimization",
      "locations": [
        "Foster City, CA",
        "Seattle, WA"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.lever.co/zoox/2ae1f38f-1b7e-4ec1-8a20-cc3816f96878",
      "verifiedAt": "2026-11-02T17:46:57+00:00",
      "sourceTextSha256": "68a41195cf8e4d381553fcf73561b0c6b37267bf2581a1aa97811ef976d1159c",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/zoox.json",
      "rawSourceFileSha256": "af11da595e335bd51385085b58eab9b3577cecac9926f2eaacec64154893a5b3",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Senior/staff technical ownership of training optimization and custom kernels, alongside roadmap and mentoring.",
      "qualification": "7+ years of total experience, including 4+ years on large-scale model training platforms, with a record of leading projects end to end.",
      "qualificationSpans": [
        {
          "text": "7+ years of total experience, including 4+ years on large-scale model training platforms, with a record of leading projects end to end.",
          "start": 2175,
          "end": 2310
        }
      ]
    },
    {
      "id": "zoox:lever:2ed8a665-cee8-4d70-bcb1-e96b6214b371",
      "employerId": "zoox",
      "employer": "Zoox",
      "title": "Senior/Staff Software Engineer, ML Inference Optimization",
      "locations": [
        "Foster City, CA",
        "Seattle, WA"
      ],
      "countries": [
        "United States"
      ],
      "url": "https://jobs.lever.co/zoox/2ed8a665-cee8-4d70-bcb1-e96b6214b371",
      "verifiedAt": "2026-11-02T17:46:57+00:00",
      "sourceTextSha256": "0901a240c2e6f1184750db2fbdca789019292c6ac1434eacd9d439e21d0e0ac2",
      "rawSourceFile": "research/physical-ai/2026-11-02/raw/zoox.json",
      "rawSourceFileSha256": "af11da595e335bd51385085b58eab9b3577cecac9926f2eaacec64154893a5b3",
      "reviewedAt": "2026-11-09",
      "reviewMethod": "Full stored-source contextual review; original classification unchanged.",
      "originalReviewStatus": "machine-screened",
      "scope": "Senior/staff inference optimization with technical leadership. No explicit direct-report or hiring responsibility stated.",
      "qualification": "Strong experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.",
      "qualificationSpans": [
        {
          "text": "Strong experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.",
          "start": 2410,
          "end": 2526
        }
      ]
    }
  ]
}
