diff --git a/app/tasks/ml.py b/app/tasks/ml.py
index 77bd9e5..61d8cf6 100644
--- a/app/tasks/ml.py
+++ b/app/tasks/ml.py
@@ -5,6 +5,7 @@ import os
 import time
 
 import numpy as np
+from celery.exceptions import SoftTimeLimitExceeded
 from sqlalchemy import and_, func
 from sqlalchemy.dialects.postgresql import insert as pg_insert
 
@@ -85,7 +86,7 @@ def _ensure_video_thumb(image) -> None:
 
 @celery.task(bind=True, name='app.tasks.ml.tag_and_embed',
              max_retries=2, default_retry_delay=60,
-             soft_time_limit=240, time_limit=360)
+             soft_time_limit=900, time_limit=1200)
 def tag_and_embed(self, image_id: int):
     """Run WD14 + SigLIP on one image (or sampled video frames) and persist results."""
     from app.ml import wd14, siglip  # lazy import so web process never loads torch
@@ -154,6 +155,17 @@ def tag_and_embed(self, image_id: int):
         kind = 'video' if is_video else 'image'
         log.info(f"tag_and_embed: {kind} {image_id} done in {t_inf:.2f}s ({len(raw)} predictions)")
         return {'status': 'ok', 'predictions': len(raw), 'duration_s': t_inf, 'kind': kind}
+    except SoftTimeLimitExceeded:
+        # Retrying a soft-time-limit hit just walks into the same wall on
+        # the next attempt — these are usually slow videos that exceed the
+        # CPU budget. Roll back, log loudly, return a terminal status so
+        # backfill stops re-enqueueing it on the next sweep.
+        db.session.rollback()
+        log.error(
+            f"tag_and_embed: soft time limit exceeded on image {image_id} "
+            f"(is_video={is_video}); not retrying",
+        )
+        return {'status': 'soft_time_limit', 'image_id': image_id, 'is_video': is_video}
     except Exception as e:
         db.session.rollback()
         log.error(f"tag_and_embed failed for image {image_id}: {e}", exc_info=True)