diff --git a/plugin/src/main/java/org/elasticsearch/xpack/ml/MachineLearning.java b/plugin/src/main/java/org/elasticsearch/xpack/ml/MachineLearning.java
index e0586dfbdba..cf444f6f50b 100644
--- a/plugin/src/main/java/org/elasticsearch/xpack/ml/MachineLearning.java
+++ b/plugin/src/main/java/org/elasticsearch/xpack/ml/MachineLearning.java
@@ -149,9 +149,8 @@ public class MachineLearning extends Plugin implements ActionPlugin {
     public static final Setting<Boolean> USE_NATIVE_PROCESS_OPTION = Setting.boolSetting("useNativeProcess", true, Property.NodeScope,
             Property.Deprecated);
 
-    public static final String ALLOCATION_ENABLED_ATTR = "xpack.ml.allocation_enabled";
-    public static final Setting<Boolean> ALLOCATION_ENABLED = Setting.boolSetting("node.attr." + ALLOCATION_ENABLED_ATTR,
-            XPackSettings.MACHINE_LEARNING_ENABLED, Setting.Property.NodeScope);
+    public static final Setting<Boolean> ML_ENABLED =
+            Setting.boolSetting("node.ml", XPackSettings.MACHINE_LEARNING_ENABLED, Setting.Property.NodeScope);
     public static final Setting<Integer> CONCURRENT_JOB_ALLOCATIONS =
             Setting.intSetting("xpack.ml.node_concurrent_job_allocations", 2, 0, Property.Dynamic, Property.NodeScope);
 
@@ -175,7 +174,7 @@ public class MachineLearning extends Plugin implements ActionPlugin {
     public List<Setting<?>> getSettings() {
         return Collections.unmodifiableList(
                 Arrays.asList(USE_NATIVE_PROCESS_OPTION,
-                        ALLOCATION_ENABLED,
+                        ML_ENABLED,
                         CONCURRENT_JOB_ALLOCATIONS,
                         ProcessCtrl.DONT_PERSIST_MODEL_STATE_SETTING,
                         ProcessCtrl.MAX_ANOMALY_RECORDS_SETTING,
@@ -186,25 +185,18 @@ public class MachineLearning extends Plugin implements ActionPlugin {
 
     @Override
     public Settings additionalSettings() {
-        Settings.Builder additionalSettings = Settings.builder();
-        Boolean allocationEnabled = settings.getAsBoolean(ALLOCATION_ENABLED.getKey(), null);
-        if (enabled == false) {
-            if (allocationEnabled != null) {
-                // if the ml plugin has been disabled the ml allocation enabled node attribute shouldn't be set,
-                // otherwise other nodes will allocate jobs to this node and that will fail, because ml hasn't been loaded.
-                throw new IllegalArgumentException("Can't specify [" + ALLOCATION_ENABLED.getKey() + "] to true when [" +
-                        XPackSettings.MACHINE_LEARNING_ENABLED.getKey() + "] has been set to false");
-            }
+        if (enabled == false || this.transportClientMode) {
             return super.additionalSettings();
         }
-        if (allocationEnabled == null) {
-            // Make sure that we explicitly set allocation enabled node attribute if it has been specified in the node
-            // settings. So we can always rely on it during assigning job tasks to nodes.
-            additionalSettings.put(ALLOCATION_ENABLED.getKey(), ALLOCATION_ENABLED.get(settings));
+
+        Settings.Builder additionalSettings = Settings.builder();
+        additionalSettings.put(super.additionalSettings());
+        Boolean allocationEnabled = ML_ENABLED.get(settings);
+        if (allocationEnabled != null && allocationEnabled) {
+            // Copy max_running_jobs setting to node attribute, so that we use this information when assigning job tasks to nodes:
+            additionalSettings.put("node.attr." + AutodetectProcessManager.MAX_RUNNING_JOBS_PER_NODE.getKey(),
+                    AutodetectProcessManager.MAX_RUNNING_JOBS_PER_NODE.get(settings));
         }
-        // Add max running job limit as node attribute so that we use this information assigning job tasks to nodes
-        additionalSettings.put("node.attr." + AutodetectProcessManager.MAX_RUNNING_JOBS_PER_NODE.getKey(),
-                AutodetectProcessManager.MAX_RUNNING_JOBS_PER_NODE.get(settings));
         return additionalSettings.build();
     }
 
diff --git a/plugin/src/main/java/org/elasticsearch/xpack/ml/action/OpenJobAction.java b/plugin/src/main/java/org/elasticsearch/xpack/ml/action/OpenJobAction.java
index 6720b233cc0..7b0f2c8e051 100644
--- a/plugin/src/main/java/org/elasticsearch/xpack/ml/action/OpenJobAction.java
+++ b/plugin/src/main/java/org/elasticsearch/xpack/ml/action/OpenJobAction.java
@@ -376,8 +376,8 @@ public class OpenJobAction extends Action<OpenJobAction.Request, PersistentActio
         PersistentTasksInProgress persistentTasksInProgress = clusterState.getMetaData().custom(PersistentTasksInProgress.TYPE);
         for (DiscoveryNode node : clusterState.getNodes()) {
             Map<String, String> nodeAttributes = node.getAttributes();
-            String allocationEnabled = nodeAttributes.get(MachineLearning.ALLOCATION_ENABLED_ATTR);
-            if ("true".equals(allocationEnabled) == false) {
+            String maxNumberOfOpenJobsStr = nodeAttributes.get(AutodetectProcessManager.MAX_RUNNING_JOBS_PER_NODE.getKey());
+            if (maxNumberOfOpenJobsStr == null) {
                 String reason = "Not opening job [" + jobId + "] on node [" + node + "], because this node isn't a ml node.";
                 logger.debug(reason);
                 reasons.add(reason);
@@ -410,7 +410,7 @@ public class OpenJobAction extends Action<OpenJobAction.Request, PersistentActio
                 continue;
             }
 
-            long maxNumberOfOpenJobs = Long.parseLong(node.getAttributes().get(MAX_RUNNING_JOBS_PER_NODE.getKey()));
+            long maxNumberOfOpenJobs = Long.parseLong(maxNumberOfOpenJobsStr);
             long available = maxNumberOfOpenJobs - numberOfAssignedJobs;
             if (available == 0) {
                 String reason = "Not opening job [" + jobId + "] on node [" + node + "], because this node is full. " +
diff --git a/plugin/src/test/java/org/elasticsearch/xpack/ml/action/OpenJobActionTests.java b/plugin/src/test/java/org/elasticsearch/xpack/ml/action/OpenJobActionTests.java
index bad37303bd1..a29b3cdcf57 100644
--- a/plugin/src/test/java/org/elasticsearch/xpack/ml/action/OpenJobActionTests.java
+++ b/plugin/src/test/java/org/elasticsearch/xpack/ml/action/OpenJobActionTests.java
@@ -15,7 +15,6 @@ import org.elasticsearch.cluster.node.DiscoveryNode;
 import org.elasticsearch.cluster.node.DiscoveryNodes;
 import org.elasticsearch.common.transport.TransportAddress;
 import org.elasticsearch.test.ESTestCase;
-import org.elasticsearch.xpack.ml.MachineLearning;
 import org.elasticsearch.xpack.ml.job.config.Job;
 import org.elasticsearch.xpack.ml.job.config.JobState;
 import org.elasticsearch.xpack.ml.MlMetadata;
@@ -96,7 +95,6 @@ public class OpenJobActionTests extends ESTestCase {
 
     public void testSelectLeastLoadedMlNode() {
         Map<String, String> nodeAttr = new HashMap<>();
-        nodeAttr.put(MachineLearning.ALLOCATION_ENABLED_ATTR, "true");
         nodeAttr.put(MAX_RUNNING_JOBS_PER_NODE.getKey(), "10");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
                 .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
@@ -128,7 +126,6 @@ public class OpenJobActionTests extends ESTestCase {
         int maxRunningJobsPerNode = randomIntBetween(1, 100);
 
         Map<String, String> nodeAttr = new HashMap<>();
-        nodeAttr.put(MachineLearning.ALLOCATION_ENABLED_ATTR, "true");
         nodeAttr.put(MAX_RUNNING_JOBS_PER_NODE.getKey(), String.valueOf(maxRunningJobsPerNode));
         DiscoveryNodes.Builder nodes = DiscoveryNodes.builder();
         Map<Long, PersistentTaskInProgress<?>> taskMap = new HashMap<>();
@@ -152,14 +149,11 @@ public class OpenJobActionTests extends ESTestCase {
     }
 
     public void testSelectLeastLoadedMlNode_noMlNodes() {
-        Map<String, String> nodeAttr = new HashMap<>();
-        nodeAttr.put(MachineLearning.ALLOCATION_ENABLED_ATTR, "false");
-        nodeAttr.put(MAX_RUNNING_JOBS_PER_NODE.getKey(), "10");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
                 .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                        nodeAttr, Collections.emptySet(), Version.CURRENT))
+                        Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
                 .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                        nodeAttr, Collections.emptySet(), Version.CURRENT))
+                        Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
                 .build();
 
         PersistentTaskInProgress<OpenJobAction.Request> task =
@@ -175,7 +169,6 @@ public class OpenJobActionTests extends ESTestCase {
 
     public void testSelectLeastLoadedMlNode_maxConcurrentOpeningJobs() {
         Map<String, String> nodeAttr = new HashMap<>();
-        nodeAttr.put(MachineLearning.ALLOCATION_ENABLED_ATTR, "true");
         nodeAttr.put(MAX_RUNNING_JOBS_PER_NODE.getKey(), "10");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
                 .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
diff --git a/plugin/src/test/java/org/elasticsearch/xpack/ml/integration/BasicDistributedJobsIT.java b/plugin/src/test/java/org/elasticsearch/xpack/ml/integration/BasicDistributedJobsIT.java
index b2c12c7b0fd..2528603f28b 100644
--- a/plugin/src/test/java/org/elasticsearch/xpack/ml/integration/BasicDistributedJobsIT.java
+++ b/plugin/src/test/java/org/elasticsearch/xpack/ml/integration/BasicDistributedJobsIT.java
@@ -140,11 +140,11 @@ public class BasicDistributedJobsIT extends BaseMlIntegTestCase {
     public void testDedicatedMlNode() throws Exception {
         internalCluster().ensureAtMostNumDataNodes(0);
         // start 2 non ml node that will never get a job allocated. (but ml apis are accessable from this node)
-        internalCluster().startNode(Settings.builder().put(MachineLearning.ALLOCATION_ENABLED.getKey(), false));
-        internalCluster().startNode(Settings.builder().put(MachineLearning.ALLOCATION_ENABLED.getKey(), false));
+        internalCluster().startNode(Settings.builder().put(MachineLearning.ML_ENABLED.getKey(), false));
+        internalCluster().startNode(Settings.builder().put(MachineLearning.ML_ENABLED.getKey(), false));
         // start ml node
         if (randomBoolean()) {
-            internalCluster().startNode(Settings.builder().put(MachineLearning.ALLOCATION_ENABLED.getKey(), true));
+            internalCluster().startNode(Settings.builder().put(MachineLearning.ML_ENABLED.getKey(), true));
         } else {
             // the default is based on 'xpack.ml.enabled', which is enabled in base test class.
             internalCluster().startNode();
@@ -165,14 +165,13 @@ public class BasicDistributedJobsIT extends BaseMlIntegTestCase {
 
             DiscoveryNode node = clusterState.nodes().resolveNode(task.getExecutorNode());
             Map<String, String> expectedNodeAttr = new HashMap<>();
-            expectedNodeAttr.put(MachineLearning.ALLOCATION_ENABLED_ATTR, "true");
             expectedNodeAttr.put(MAX_RUNNING_JOBS_PER_NODE.getKey(), "10");
             assertEquals(expectedNodeAttr, node.getAttributes());
             assertEquals(JobState.OPENED, task.getStatus());
         });
 
         logger.info("stop the only running ml node");
-        internalCluster().stopRandomNode(settings -> settings.getAsBoolean(MachineLearning.ALLOCATION_ENABLED.getKey(), true));
+        internalCluster().stopRandomNode(settings -> settings.getAsBoolean(MachineLearning.ML_ENABLED.getKey(), true));
         ensureStableCluster(2);
         assertBusy(() -> {
             // job should get and remain in a failed state:
@@ -186,7 +185,7 @@ public class BasicDistributedJobsIT extends BaseMlIntegTestCase {
         });
 
         logger.info("start ml node");
-        internalCluster().startNode(Settings.builder().put(MachineLearning.ALLOCATION_ENABLED.getKey(), true));
+        internalCluster().startNode(Settings.builder().put(MachineLearning.ML_ENABLED.getKey(), true));
         ensureStableCluster(3);
         assertBusy(() -> {
             // job should be re-opened:
@@ -197,7 +196,6 @@ public class BasicDistributedJobsIT extends BaseMlIntegTestCase {
             assertNotNull(task.getExecutorNode());
             DiscoveryNode node = clusterState.nodes().resolveNode(task.getExecutorNode());
             Map<String, String> expectedNodeAttr = new HashMap<>();
-            expectedNodeAttr.put(MachineLearning.ALLOCATION_ENABLED_ATTR, "true");
             expectedNodeAttr.put(MAX_RUNNING_JOBS_PER_NODE.getKey(), "10");
             assertEquals(expectedNodeAttr, node.getAttributes());
             assertEquals(JobState.OPENED, task.getStatus());
@@ -211,12 +209,12 @@ public class BasicDistributedJobsIT extends BaseMlIntegTestCase {
         // start non ml node, but that will hold the indices
         logger.info("Start non ml node:");
         String nonMlNode = internalCluster().startNode(Settings.builder()
-                .put(MachineLearning.ALLOCATION_ENABLED.getKey(), false));
+                .put(MachineLearning.ML_ENABLED.getKey(), false));
         logger.info("Starting ml nodes");
         internalCluster().startNodes(numMlNodes, Settings.builder()
                 .put("node.data", false)
                 .put("node.master", false)
-                .put(MachineLearning.ALLOCATION_ENABLED.getKey(), true).build());
+                .put(MachineLearning.ML_ENABLED.getKey(), true).build());
         ensureStableCluster(numMlNodes + 1);
 
         int maxConcurrentJobAllocations = randomIntBetween(1, 4);
@@ -273,7 +271,7 @@ public class BasicDistributedJobsIT extends BaseMlIntegTestCase {
             Runnable r = () -> {
                 try {
                     internalCluster()
-                            .stopRandomNode(settings -> settings.getAsBoolean(MachineLearning.ALLOCATION_ENABLED.getKey(), false));
+                            .stopRandomNode(settings -> settings.getAsBoolean(MachineLearning.ML_ENABLED.getKey(), false));
                 } catch (IOException e) {
                     logger.error("error stopping node", e);
                 }
@@ -294,7 +292,7 @@ public class BasicDistributedJobsIT extends BaseMlIntegTestCase {
         internalCluster().startNodes(numMlNodes, Settings.builder()
                 .put("node.data", false)
                 .put("node.master", false)
-                .put(MachineLearning.ALLOCATION_ENABLED.getKey(), true).build());
+                .put(MachineLearning.ML_ENABLED.getKey(), true).build());
 
         ensureStableCluster(1 + numMlNodes);
         assertBusy(() -> {