diff --git a/.github/scripts/tests_to_skip.txt b/.github/scripts/tests_to_skip.txt
new file mode 100644
index 000000000..7c0e95f00
--- /dev/null
+++ b/.github/scripts/tests_to_skip.txt
@@ -0,0 +1 @@
+_disabled_in_oss_compatibility
diff --git a/.github/workflows/unittest_ci_cpu.yml b/.github/workflows/unittest_ci_cpu.yml
index df8c74ecc..0c53bbe7d 100644
--- a/.github/workflows/unittest_ci_cpu.yml
+++ b/.github/workflows/unittest_ci_cpu.yml
@@ -72,6 +72,14 @@ jobs:
           python -c "import numpy"
         echo "numpy succeeded"
         conda install -n build_binary -y pytest
+        # Read the list of tests to skip from a file, ignoring empty lines and comments
+        skip_expression=$(awk '!/^($|#)/ {printf " and not %s", $0}' ./.github/scripts/tests_to_skip.txt)
+        # Check if skip_expression is effectively empty
+        if [ -z "$skip_expression" ]; then
+          skip_expression=""
+        else
+          skip_expression=${skip_expression:5}  # Remove the leading " and "
+        fi
         conda run -n build_binary \
           python -m pytest torchrec -v -s -W ignore::pytest.PytestCollectionWarning --continue-on-collection-errors \
-          --ignore-glob=**/test_utils/
+          --ignore-glob=**/test_utils/ -k "$skip_expression"
diff --git a/torchrec/ir/tests/test_serializer.py b/torchrec/ir/tests/test_serializer.py
index 90bde12ca..a997a288d 100644
--- a/torchrec/ir/tests/test_serializer.py
+++ b/torchrec/ir/tests/test_serializer.py
@@ -253,13 +253,7 @@ def test_serialize_deserialize_ebc(self) -> None:
             self.assertEqual(deserialized.shape, orginal.shape)
             self.assertTrue(torch.allclose(deserialized, orginal))
 
-    # pyre-ignore[56]: Pyre was not able to infer the type of argument
-    @unittest.skipIf(
-        torch.cuda.device_count() == 0,
-        "skip this test in OSS (no GPU available) because torch.export uses training ir in OSS",
-    )
-    def test_dynamic_shape_ebc(self) -> None:
-        # TODO: https://fb.workplace.com/groups/1028545332188949/permalink/1138699244506890/
+    def test_dynamic_shape_ebc_disabled_in_oss_compatibility(self) -> None:
         model = self.generate_model()
         feature1 = KeyedJaggedTensor.from_offsets_sync(
             keys=["f1", "f2", "f3"],
diff --git a/torchrec/models/experimental/test_transformerdlrm.py b/torchrec/models/experimental/test_transformerdlrm.py
index 15bd38e02..07f49ecf2 100644
--- a/torchrec/models/experimental/test_transformerdlrm.py
+++ b/torchrec/models/experimental/test_transformerdlrm.py
@@ -61,12 +61,7 @@ def test_larger(self) -> None:
         concat_dense = inter_arch(dense_features, sparse_features)
         self.assertEqual(concat_dense.size(), (B, D * (F + 1)))
 
-    # pyre-ignore[56]: Pyre was not able to infer the type of argument
-    @unittest.skipIf(
-        torch.cuda.device_count() == 0,
-        "skip this test in OSS (no GPU available) because seed might be different in OSS",
-    )
-    def test_correctness(self) -> None:
+    def test_correctness_disabled_in_oss_compatibility(self) -> None:
         D = 4
         B = 3
         # multi-head attentions
@@ -170,12 +165,7 @@ def test_correctness(self) -> None:
             )
         )
 
-    # pyre-ignore[56]: Pyre was not able to infer the type of argument
-    @unittest.skipIf(
-        torch.cuda.device_count() == 0,
-        "skip this test in OSS (no GPU available) because seed might be different in OSS",
-    )
-    def test_numerical_stability(self) -> None:
+    def test_numerical_stability_disabled_in_oss_compatibility(self) -> None:
         D = 4
         B = 3
         # multi-head attentions
@@ -204,12 +194,7 @@ def test_numerical_stability(self) -> None:
 
 
 class DLRMTransformerTest(unittest.TestCase):
-    # pyre-ignore[56]: Pyre was not able to infer the type of argument
-    @unittest.skipIf(
-        torch.cuda.device_count() == 0,
-        "skip this test in OSS (no GPU available) because seed might be different in OSS",
-    )
-    def test_basic(self) -> None:
+    def test_basic_disabled_in_oss_compatibility(self) -> None:
         torch.manual_seed(0)
         B = 2
         D = 8