diff --git a/machine-learning/app/models/facial_recognition/detection.py b/machine-learning/app/models/facial_recognition/detection.py
index 2efacd447e..8d6a752aaa 100644
--- a/machine-learning/app/models/facial_recognition/detection.py
+++ b/machine-learning/app/models/facial_recognition/detection.py
@@ -2,6 +2,7 @@ from pathlib import Path
 from typing import Any
 
 import numpy as np
+import onnxruntime as ort
 from insightface.model_zoo import RetinaFace
 from numpy.typing import NDArray
 
@@ -26,6 +27,7 @@ class FaceDetector(InferenceModel):
 
     def _load(self) -> ModelSession:
         session = self._make_session(self.model_path)
+        self._squeeze_outputs(session)
         self.model = RetinaFace(session=session)
         self.model.prepare(ctx_id=0, det_thresh=self.min_score, input_size=(640, 640))
 
@@ -44,5 +46,15 @@ class FaceDetector(InferenceModel):
     def _detect(self, inputs: NDArray[np.uint8] | bytes) -> tuple[NDArray[np.float32], NDArray[np.float32]]:
         return self.model.detect(inputs)  # type: ignore
 
+    def _squeeze_outputs(self, session: ort.InferenceSession) -> None:
+        original_run = session.run
+
+        def run(output_names: list[str], input_feed: dict[str, NDArray[np.float32]]) -> list[NDArray[np.float32]]:
+            out: list[NDArray[np.float32]] = original_run(output_names, input_feed)
+            out = [o.squeeze(axis=0) for o in out]
+            return out
+
+        session.run = run
+
     def configure(self, **kwargs: Any) -> None:
         self.model.det_thresh = kwargs.pop("minScore", self.model.det_thresh)