diff --git a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
index e3aaaec175..98ec69eb44 100644
--- a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
+++ b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
@@ -548,6 +548,7 @@ def aten_ops_hard_sigmoid(
 
 
 @dynamo_tensorrt_converter(torch.ops.aten.matmul, supports_dynamic_shapes=True)
+@dynamo_tensorrt_converter(torch.ops.aten.dot.default, supports_dynamic_shapes=True)
 @dynamo_tensorrt_converter(torch.ops.aten.mm.default, supports_dynamic_shapes=True)
 @dynamo_tensorrt_converter(torch.ops.aten.mv.default, supports_dynamic_shapes=True)
 @dynamo_tensorrt_converter(torch.ops.aten.bmm.default, supports_dynamic_shapes=True)
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/matmul.py b/py/torch_tensorrt/dynamo/conversion/impl/matmul.py
index 5ea29622c8..77dd7ae6f5 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/matmul.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/matmul.py
@@ -1,15 +1,17 @@
 from typing import Optional
 
+import tensorrt as trt
 import torch
 from torch.fx.node import Target
 from torch_tensorrt import _enums
 from torch_tensorrt.dynamo._SourceIR import SourceIR
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
-from torch_tensorrt.dynamo.conversion.converter_utils import get_trt_tensor
-from torch_tensorrt.fx.converters.converter_utils import broadcast, set_layer_name
-from torch_tensorrt.fx.types import TRTTensor
-
-import tensorrt as trt
+from torch_tensorrt.dynamo.conversion.converter_utils import (
+    broadcast,
+    get_trt_tensor,
+    set_layer_name,
+)
+from torch_tensorrt.dynamo.types import TRTTensor
 
 
 def matrix_multiply(
@@ -43,7 +45,7 @@ def matrix_multiply(
         other_matrix_op = trt.MatrixOperation.VECTOR
 
     input, other = broadcast(
-        ctx.net, input, other, f"{name}_input", f"{name}_other", preset_diff
+        ctx, input, other, f"{name}_input", f"{name}_other", preset_diff
     )
     layer = ctx.net.add_matrix_multiply(input, input_matrix_op, other, other_matrix_op)
     set_layer_name(layer, target, name, source_ir)
diff --git a/py/torch_tensorrt/dynamo/lowering/_decomposition_groups.py b/py/torch_tensorrt/dynamo/lowering/_decomposition_groups.py
index 0a1688b295..ae3e7e1ffa 100644
--- a/py/torch_tensorrt/dynamo/lowering/_decomposition_groups.py
+++ b/py/torch_tensorrt/dynamo/lowering/_decomposition_groups.py
@@ -33,7 +33,6 @@
     aten.detach,
     aten.diag_embed,
     aten.diagonal_backward,
-    aten.dot,
     aten.elu_backward,
     aten.embedding_dense_backward,
     aten.empty_like,
diff --git a/tests/py/dynamo/conversion/test_matmul_aten.py b/tests/py/dynamo/conversion/test_matmul_aten.py
index ea39ea06f8..cf1fa36e82 100644
--- a/tests/py/dynamo/conversion/test_matmul_aten.py
+++ b/tests/py/dynamo/conversion/test_matmul_aten.py
@@ -8,6 +8,41 @@
 
 
 class TestMatMulConverter(DispatchTestCase):
+    @parameterized.expand(
+        [
+            (
+                "1_1",
+                (1,),
+                (1,),
+            ),
+            (
+                "1_1",
+                (2,),
+                (2,),
+            ),
+            (
+                "1_1",
+                (3,),
+                (3,),
+            ),
+        ]
+    )
+    def test_matmul_dot(self, _, input_shape, other_shape):
+        class MatMul(nn.Module):
+            def __init__(self):
+                super().__init__()
+                self.other = nn.Parameter(torch.randn(*other_shape))
+
+            def forward(self, input):
+                return torch.ops.aten.dot.default(input, self.other)
+
+        inputs = [torch.randn(*input_shape)]
+
+        self.run_test(
+            MatMul(),
+            inputs,
+        )
+
     @parameterized.expand(
         [
             (