diff --git a/tensorflow/compiler/mlir/xla/hlo_function_importer.cc b/tensorflow/compiler/mlir/xla/hlo_function_importer.cc
index 1da4fd04ffb..1f5d1fb2ae5 100644
--- a/tensorflow/compiler/mlir/xla/hlo_function_importer.cc
+++ b/tensorflow/compiler/mlir/xla/hlo_function_importer.cc
@@ -438,6 +438,7 @@ StatusOr<mlir::Operation*> HloFunctionImporter::ImportInstruction(
       NoAttributeCase(kAdd, AddOp);
       NoAttributeCase(kAnd, AndOp);
       NoAttributeCase(kAtan2, Atan2Op);
+      NoAttributeCase(kBitcastConvert, BitcastConvertOp);
       NoAttributeCase(kConvert, ConvertOp);
       NoAttributeCase(kClamp, ClampOp);
       NoAttributeCase(kComplex, ComplexOp);
diff --git a/tensorflow/compiler/mlir/xla/ir/hlo_ops.td b/tensorflow/compiler/mlir/xla/ir/hlo_ops.td
index 3c4fd473eb6..2d1913f8274 100644
--- a/tensorflow/compiler/mlir/xla/ir/hlo_ops.td
+++ b/tensorflow/compiler/mlir/xla/ir/hlo_ops.td
@@ -586,6 +586,14 @@ def HLO_BatchNormTrainingOp : HLO_Op<"batch_norm_training", [NoSideEffect]>,
   let results = (outs HLO_Tuple);
 }
 
+def HLO_BitcastConvertOp : HLO_Op<"bitcast_convert",
+    [NoSideEffect, SameOperandsAndResultShape]>, BASE_HLO_BitcastConvertOp {
+
+  let arguments = (ins HLO_Tensor:$operand);
+  let results = (outs HLO_Tensor);
+  let hasCustomHLOConverter = 1;
+}
+
 def HLO_BroadcastOp : HLO_Op<"broadcast",
       [NoSideEffect, SameOperandsAndResultElementType]>, BASE_HLO_BroadcastOp {
   let arguments = (ins
diff --git a/tensorflow/compiler/mlir/xla/ir/hlo_ops_base.td b/tensorflow/compiler/mlir/xla/ir/hlo_ops_base.td
index a6d4210b60c..3be2c26a1bf 100644
--- a/tensorflow/compiler/mlir/xla/ir/hlo_ops_base.td
+++ b/tensorflow/compiler/mlir/xla/ir/hlo_ops_base.td
@@ -656,6 +656,20 @@ class BASE_HLO_BatchNormTrainingOp {
   }];
 }
 
+class BASE_HLO_BitcastConvertOp {
+  string summary = "BitcastConvert operator";
+
+  string description = [{
+    Similar to a 'tf.bitcast' in TensorFlow, performs an element-wise bitcast
+    operation from a data shape to a target shape. The dimensions must match,
+    and the conversion is an element-wise one. Bitcast is implemented as a
+    low-level cast, so machines with different floating-point representations
+    will give different results.
+
+    See https://www.tensorflow.org/xla/operation_semantics#bitcastconverttype.
+  }];
+}
+
 class BASE_HLO_BroadcastOp  {
   string summary = "Broadcast a tensor to a higher rank by prepending dimensions";
 
diff --git a/tensorflow/compiler/mlir/xla/mlir_hlo_to_hlo.cc b/tensorflow/compiler/mlir/xla/mlir_hlo_to_hlo.cc
index 26cd512aa85..c7501a91dd9 100644
--- a/tensorflow/compiler/mlir/xla/mlir_hlo_to_hlo.cc
+++ b/tensorflow/compiler/mlir/xla/mlir_hlo_to_hlo.cc
@@ -446,6 +446,14 @@ LogicalResult ExportXlaOp(AllReduceOp op, OpLoweringContext ctx) {
   return success();
 }
 
+LogicalResult ExportXlaOp(BitcastConvertOp op, OpLoweringContext ctx) {
+  auto& value_map = *ctx.values;
+  value_map[op] = xla::BitcastConvertType(
+      value_map[op.operand()],
+      xla::TypeToPrimitiveType(getElementTypeOrSelf(op.getType())));
+  return success();
+}
+
 LogicalResult ExportXlaOp(BroadcastInDimOp op, OpLoweringContext ctx) {
   auto type = op.getType().dyn_cast<RankedTensorType>();
   if (!type) return failure();
diff --git a/tensorflow/compiler/mlir/xla/tests/translate/export.mlir b/tensorflow/compiler/mlir/xla/tests/translate/export.mlir
index 85ed317f8c6..ff9d69b9a52 100644
--- a/tensorflow/compiler/mlir/xla/tests/translate/export.mlir
+++ b/tensorflow/compiler/mlir/xla/tests/translate/export.mlir
@@ -111,6 +111,18 @@ func @main(%arg0: tensor<1x4xi32>, %arg1: tensor<2x4xi32>, %arg2: tensor<2x3x4xi
 
 // -----
 
+// CHECK-LABEL:  HloModule
+func @main(%arg0: tensor<2xi32>) -> tensor<2xf32> {
+  %0 = "xla_hlo.bitcast_convert"(%arg0) : (tensor<2xi32>) -> tensor<2xf32>
+  return %0 : tensor<2xf32>
+}
+
+// CHECK-LABEL:  ENTRY
+// CHECK:  %[[ARG:.*]] = s32[2] parameter(0)
+// CHECK:  ROOT %[[RESULT:.*]] = f32[2] bitcast-convert(s32[2] %[[ARG]])
+
+// -----
+
 // CHECK-LABEL:  HloModule
 func @main(%arg0: tensor<4xi32>) -> tensor<1x2x3x4xi32> {
   // CHECK:  [[ARG:%.*]] = s32[4] parameter(0)