diff --git a/torchrec/schema/api_tests/test_embedding_config_schema.py b/torchrec/schema/api_tests/test_embedding_config_schema.py
new file mode 100644
index 000000000..8baefe4e7
--- /dev/null
+++ b/torchrec/schema/api_tests/test_embedding_config_schema.py
@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-strict
+
+import inspect
+import unittest
+from dataclasses import dataclass, field
+from typing import Callable, List, Optional
+
+import torch
+from torchrec.modules.embedding_configs import (
+    DataType,
+    EmbeddingBagConfig,
+    EmbeddingConfig,
+    PoolingType,
+)
+
+from torchrec.schema.utils import is_signature_compatible
+
+
+@dataclass
+class StableEmbeddingBagConfig:
+    num_embeddings: int
+    embedding_dim: int
+    name: str = ""
+    data_type: DataType = DataType.FP32
+    feature_names: List[str] = field(default_factory=list)
+    weight_init_max: Optional[float] = None
+    weight_init_min: Optional[float] = None
+    num_embeddings_post_pruning: Optional[int] = None
+
+    init_fn: Optional[Callable[[torch.Tensor], Optional[torch.Tensor]]] = None
+    # when the position_weighted feature is in this table config,
+    # enable this flag to support rw_sharding
+    need_pos: bool = False
+    pooling: PoolingType = PoolingType.SUM
+
+
+@dataclass
+class StableEmbeddingConfig:
+    num_embeddings: int
+    embedding_dim: int
+    name: str = ""
+    data_type: DataType = DataType.FP32
+    feature_names: List[str] = field(default_factory=list)
+    weight_init_max: Optional[float] = None
+    weight_init_min: Optional[float] = None
+    num_embeddings_post_pruning: Optional[int] = None
+
+    init_fn: Optional[Callable[[torch.Tensor], Optional[torch.Tensor]]] = None
+    # when the position_weighted feature is in this table config,
+    # enable this flag to support rw_sharding
+    need_pos: bool = False
+
+
+class TestEmbeddingConfig(unittest.TestCase):
+    def test_embedding_bag_config(self) -> None:
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingBagConfig.__init__),
+                inspect.signature(EmbeddingBagConfig.__init__),
+            )
+        )
+
+    def test_embedding_config(self) -> None:
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingConfig.__init__),
+                inspect.signature(EmbeddingConfig.__init__),
+            )
+        )
diff --git a/torchrec/schema/api_tests/test_embedding_module_schema.py b/torchrec/schema/api_tests/test_embedding_module_schema.py
new file mode 100644
index 000000000..6beeba0d3
--- /dev/null
+++ b/torchrec/schema/api_tests/test_embedding_module_schema.py
@@ -0,0 +1,159 @@
+#!/usr/bin/env python3
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-strict
+
+import inspect
+import unittest
+from typing import Dict, List, Optional
+
+import torch
+from torchrec.modules.embedding_configs import EmbeddingBagConfig, EmbeddingConfig
+from torchrec.modules.embedding_modules import (
+    EmbeddingBagCollection,
+    EmbeddingCollection,
+)
+
+from torchrec.schema.utils import is_signature_compatible
+from torchrec.sparse.jagged_tensor import JaggedTensor, KeyedJaggedTensor, KeyedTensor
+
+
+class StableEmbeddingBagCollectionInterface:
+    """
+    Stable Interface for `EmbeddingBagCollection`.
+    """
+
+    def __init__(
+        self,
+        tables: List[EmbeddingBagConfig],
+        is_weighted: bool = False,
+        device: Optional[torch.device] = None,
+    ) -> None:
+        pass
+
+    def forward(
+        self,
+        features: KeyedJaggedTensor,
+    ) -> KeyedTensor:
+        return KeyedTensor(
+            keys=[],
+            length_per_key=[],
+            values=torch.empty(0),
+        )
+
+    def embedding_bag_configs(
+        self,
+    ) -> List[EmbeddingBagConfig]:
+        return []
+
+    def is_weighted(self) -> bool:
+        return False
+
+
+class StableEmbeddingCollectionInterface:
+    """
+    Stable Interface for `EmbeddingBagCollection`.
+    """
+
+    def __init__(
+        self,
+        tables: List[EmbeddingConfig],
+        device: Optional[torch.device] = None,
+        need_indices: bool = False,
+    ) -> None:
+        return
+
+    def forward(
+        self,
+        features: KeyedJaggedTensor,
+    ) -> Dict[str, JaggedTensor]:
+        return {}
+
+    def embedding_configs(
+        self,
+    ) -> List[EmbeddingConfig]:
+        return []
+
+    def need_indices(self) -> bool:
+        return False
+
+    def embedding_dim(self) -> int:
+        return 0
+
+    def embedding_names_by_table(self) -> List[List[str]]:
+        return []
+
+
+class TestEmbeddingConfig(unittest.TestCase):
+    def test_embedding_bag_collection(self) -> None:
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingBagCollectionInterface.__init__),
+                inspect.signature(EmbeddingBagCollection.__init__),
+            )
+        )
+
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingBagCollectionInterface.forward),
+                inspect.signature(EmbeddingBagCollection.forward),
+            )
+        )
+
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(
+                    StableEmbeddingBagCollectionInterface.embedding_bag_configs
+                ),
+                inspect.signature(EmbeddingBagCollection.embedding_bag_configs),
+            )
+        )
+
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingBagCollectionInterface.is_weighted),
+                inspect.signature(EmbeddingBagCollection.is_weighted),
+            )
+        )
+
+    def test_embedding_collection(self) -> None:
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingCollectionInterface.__init__),
+                inspect.signature(EmbeddingCollection.__init__),
+            )
+        )
+
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingCollectionInterface.forward),
+                inspect.signature(EmbeddingCollection.forward),
+            )
+        )
+
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingCollectionInterface.embedding_configs),
+                inspect.signature(EmbeddingCollection.embedding_configs),
+            )
+        )
+
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(StableEmbeddingCollectionInterface.embedding_dim),
+                inspect.signature(EmbeddingCollection.embedding_dim),
+            )
+        )
+
+        self.assertTrue(
+            is_signature_compatible(
+                inspect.signature(
+                    StableEmbeddingCollectionInterface.embedding_names_by_table
+                ),
+                inspect.signature(EmbeddingCollection.embedding_names_by_table),
+            )
+        )