diff --git a/R/AutoTuner.R b/R/AutoTuner.R
index 3f7da6f2..33d3771f 100644
--- a/R/AutoTuner.R
+++ b/R/AutoTuner.R
@@ -159,6 +159,7 @@ AutoTuner = R6Class("AutoTuner",
 
       ia$check_values = assert_flag(check_values)
       ia$callbacks = assert_callbacks(as_callbacks(callbacks))
+      if (!is.null(rush)) ia$rush = assert_class(rush, "Rush")
       self$instance_args = ia
 
       super$initialize(
diff --git a/R/ObjectiveTuning.R b/R/ObjectiveTuning.R
index 0d623d0c..ce47d7ac 100644
--- a/R/ObjectiveTuning.R
+++ b/R/ObjectiveTuning.R
@@ -60,8 +60,8 @@ ObjectiveTuning = R6Class("ObjectiveTuning",
       self$measures = assert_measures(as_measures(measures), task = self$task, learner = self$learner)
       self$store_models = assert_flag(store_models)
       self$store_benchmark_result = assert_flag(store_benchmark_result) || self$store_models
-
       self$callbacks = assert_callbacks(as_callbacks(callbacks))
+
       self$default_values = self$learner$param_set$values
 
       super$initialize(
diff --git a/R/auto_tuner.R b/R/auto_tuner.R
index 910913cf..8bcf0c03 100644
--- a/R/auto_tuner.R
+++ b/R/auto_tuner.R
@@ -21,6 +21,7 @@
 #' @template param_store_models
 #' @template param_check_values
 #' @template param_callbacks
+#' @template param_rush
 #'
 #' @export
 #' @examples
@@ -45,7 +46,8 @@ auto_tuner = function(
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
-  callbacks = NULL
+  callbacks = NULL,
+  rush = NULL
   ) {
   terminator = terminator %??% terminator_selection(term_evals, term_time)
 
@@ -60,5 +62,6 @@ auto_tuner = function(
     store_benchmark_result = store_benchmark_result,
     store_models = store_models,
     check_values = check_values,
-    callbacks = callbacks)
+    callbacks = callbacks,
+    rush = rush)
 }
diff --git a/man/AutoTuner.Rd b/man/AutoTuner.Rd
index 6cc2d9e7..dde825d2 100644
--- a/man/AutoTuner.Rd
+++ b/man/AutoTuner.Rd
@@ -176,7 +176,6 @@ Hash (unique identifier) for this partial object, excluding some components whic
 \if{html}{\out{
 <details><summary>Inherited methods</summary>
 <ul>
-<li><span class="pkg-link" data-pkg="mlr3" data-topic="Learner" data-id="estimate_memory_usage"><a href='../../mlr3/html/Learner.html#method-Learner-estimate_memory_usage'><code>mlr3::Learner$estimate_memory_usage()</code></a></span></li>
 <li><span class="pkg-link" data-pkg="mlr3" data-topic="Learner" data-id="format"><a href='../../mlr3/html/Learner.html#method-Learner-format'><code>mlr3::Learner$format()</code></a></span></li>
 <li><span class="pkg-link" data-pkg="mlr3" data-topic="Learner" data-id="help"><a href='../../mlr3/html/Learner.html#method-Learner-help'><code>mlr3::Learner$help()</code></a></span></li>
 <li><span class="pkg-link" data-pkg="mlr3" data-topic="Learner" data-id="predict"><a href='../../mlr3/html/Learner.html#method-Learner-predict'><code>mlr3::Learner$predict()</code></a></span></li>
diff --git a/man/auto_tuner.Rd b/man/auto_tuner.Rd
index 293af905..c3047ff3 100644
--- a/man/auto_tuner.Rd
+++ b/man/auto_tuner.Rd
@@ -17,7 +17,8 @@ auto_tuner(
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
-  callbacks = NULL
+  callbacks = NULL,
+  rush = NULL
 )
 }
 \arguments{
@@ -73,6 +74,9 @@ computational overhead is reduced.}
 
 \item{callbacks}{(list of \link{Callback})\cr
 List of callbacks.}
+
+\item{rush}{(\code{Rush})\cr
+If a rush instance is supplied, the tuning runs without batches.}
 }
 \value{
 \link{AutoTuner}.
diff --git a/tests/testthat/test_auto_tuner.R b/tests/testthat/test_auto_tuner.R
index ae886855..37cc8409 100644
--- a/tests/testthat/test_auto_tuner.R
+++ b/tests/testthat/test_auto_tuner.R
@@ -20,3 +20,46 @@ test_that("auto_tuner function works", {
   expect_class(at, "AutoTuner")
   expect_class(at$instance_args$terminator, "TerminatorCombo")
 })
+
+test_that("async auto tuner works", {
+  skip_if_not_installed("rush")
+  flush_redis()
+
+  rush_plan(n_workers = 2)
+
+  at = auto_tuner(
+    tuner = tnr("async_random_search"),
+    learner = lrn("classif.rpart", cp = to_tune(0.01, 0.1)),
+    resampling = rsmp("cv", folds = 3),
+    measure = msr("classif.ce"),
+    terminator = trm("evals", n_evals = 3)
+  )
+
+  expect_class(at, "AutoTuner")
+  at$train(tsk("pima"))
+
+  expect_class(at$tuning_instance, "TuningInstanceAsyncSingleCrit")
+})
+
+test_that("async auto tuner works with rush controller", {
+  skip_if_not_installed("rush")
+  flush_redis()
+
+  rush_plan(n_workers = 2)
+  rush = rsh(network_id = "tuning_network")
+
+  at = auto_tuner(
+    tuner = tnr("async_random_search"),
+    learner = lrn("classif.rpart", cp = to_tune(0.01, 0.1)),
+    resampling = rsmp("cv", folds = 3),
+    measure = msr("classif.ce"),
+    terminator = trm("evals", n_evals = 3),
+    rush = rush
+  )
+
+  expect_class(at, "AutoTuner")
+  expect_class(at$instance_args$rush, "Rush")
+  at$train(tsk("pima"))
+
+  expect_class(at$tuning_instance, "TuningInstanceAsyncSingleCrit")
+})