diff --git a/common/src/main/java/org/opensearch/ml/common/output/MLPredictionOutput.java b/common/src/main/java/org/opensearch/ml/common/output/MLPredictionOutput.java
index 1b8eb8bd6c..830a19623a 100644
--- a/common/src/main/java/org/opensearch/ml/common/output/MLPredictionOutput.java
+++ b/common/src/main/java/org/opensearch/ml/common/output/MLPredictionOutput.java
@@ -30,6 +30,8 @@ public class MLPredictionOutput extends MLOutput {
     public static final String TASK_ID_FIELD = "task_id";
     public static final String STATUS_FIELD = "status";
     public static final String PREDICTION_RESULT_FIELD = "prediction_result";
+
+    // This field will be created for offline batch prediction tasks containing details of the batch job as outputted by the remote server.
     public static final String REMOTE_JOB_FIELD = "remote_job";
 
     String taskId;
diff --git a/common/src/test/java/org/opensearch/ml/common/output/MLPredictionOutputTest.java b/common/src/test/java/org/opensearch/ml/common/output/MLPredictionOutputTest.java
index 857e92f5a3..49a1e9355b 100644
--- a/common/src/test/java/org/opensearch/ml/common/output/MLPredictionOutputTest.java
+++ b/common/src/test/java/org/opensearch/ml/common/output/MLPredictionOutputTest.java
@@ -9,7 +9,9 @@
 
 import java.io.IOException;
 import java.util.ArrayList;
+import java.util.HashMap;
 import java.util.List;
+import java.util.Map;
 
 import org.junit.Before;
 import org.junit.Test;
@@ -30,6 +32,7 @@
 public class MLPredictionOutputTest {
 
     MLPredictionOutput output;
+    MLPredictionOutput outputWithRemoteJob;
 
     @Before
     public void setUp() {
@@ -38,12 +41,17 @@ public void setUp() {
         rows.add(new Row(new ColumnValue[] { new IntValue(1) }));
         rows.add(new Row(new ColumnValue[] { new IntValue(2) }));
         DataFrame dataFrame = new DefaultDataFrame(columnMetas, rows);
+        Map<String, Object> remoteJob = new HashMap<>();
+        remoteJob.put("status", "INPROGRESS");
+        remoteJob.put("job_id", "testJobID");
         output = MLPredictionOutput.builder().taskId("test_task_id").status("test_status").predictionResult(dataFrame).build();
+        outputWithRemoteJob = new MLPredictionOutput("test_task_id", "test_status", remoteJob);
     }
 
     @Test
     public void toXContent() throws IOException {
         XContentBuilder builder = MediaTypeRegistry.contentBuilder(XContentType.JSON);
+        XContentBuilder builderWithRemoteJob = MediaTypeRegistry.contentBuilder(XContentType.JSON);
         output.toXContent(builder, ToXContent.EMPTY_PARAMS);
         String jsonStr = builder.toString();
         assertEquals(
@@ -53,6 +61,12 @@ public void toXContent() throws IOException {
                 + "\"value\":2}]}]}}",
             jsonStr
         );
+        outputWithRemoteJob.toXContent(builderWithRemoteJob, ToXContent.EMPTY_PARAMS);
+        String jsonStr2 = builderWithRemoteJob.toString();
+        assertEquals(
+            "{\"task_id\":\"test_task_id\",\"status\":\"test_status\",\"remote_job\":{\"job_id\":\"testJobID\",\"status\":\"INPROGRESS\"}}",
+            jsonStr2
+        );
     }
 
     @Test