diff --git a/tensorflow/python/tpu/tpu_strategy_util.py b/tensorflow/python/tpu/tpu_strategy_util.py
index 0f2f93deac5..6b62f55b5bf 100644
--- a/tensorflow/python/tpu/tpu_strategy_util.py
+++ b/tensorflow/python/tpu/tpu_strategy_util.py
@@ -23,6 +23,7 @@ from tensorflow.python.client import session as session_lib
 from tensorflow.python.distribute.cluster_resolver import TPUClusterResolver
 from tensorflow.python.eager import context
 from tensorflow.python.eager import function
+from tensorflow.python.framework import device
 from tensorflow.python.framework import ops
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.tpu import topology
@@ -48,7 +49,15 @@ def initialize_tpu_system(cluster_resolver=None):
   Raises:
     RuntimeError: If no TPU devices found for eager execution.
   """
+  job = None
   if cluster_resolver is None:
+    # If no cluster resolver is specified, and running eagerly, execute the init
+    # ops in the current device scope.
+    if context.executing_eagerly():
+      curr_device = device.DeviceSpec.from_string(context.context().device_name)
+      if curr_device.job is not None:
+        job = "{}/replica:0/task:0".format(curr_device.job)
+
     cluster_resolver = TPUClusterResolver("")
   assert isinstance(cluster_resolver, TPUClusterResolver)
 
@@ -66,7 +75,6 @@ def initialize_tpu_system(cluster_resolver=None):
     # DistributedTPURewritePass. This pass actually adds real ops that
     # initialize the TPU system. Thus, we can't simply run tpu.initialize_system
     # eagerly. We need to wrap it in defun and trigger the rewrite passes on it.
-    job = None
     if tpu_name not in _LOCAL_MASTERS:
       # Explicitly place the tpu.initialize_system in the first worker to
       # avoid the output node match multiple devices error.