diff --git a/benchmarks/bench_saga.py b/benchmarks/bench_saga.py
index 581f7e3881e9e..340549ef240e1 100644
--- a/benchmarks/bench_saga.py
+++ b/benchmarks/bench_saga.py
@@ -7,8 +7,7 @@
 import time
 import os
 
-from joblib import Parallel
-from sklearn.utils.fixes import delayed
+from sklearn.utils.parallel import delayed, Parallel
 import matplotlib.pyplot as plt
 import numpy as np
 
diff --git a/build_tools/azure/linting.sh b/build_tools/azure/linting.sh
index 21ef53c8012dc..9cc57c5f06066 100755
--- a/build_tools/azure/linting.sh
+++ b/build_tools/azure/linting.sh
@@ -34,10 +34,15 @@ then
     exit 1
 fi
 
-joblib_import="$(git grep -l -A 10 -E "joblib import.+delayed" -- "*.py" ":!sklearn/utils/_joblib.py" ":!sklearn/utils/fixes.py")"
-
-if [ ! -z "$joblib_import" ]; then
-    echo "Use from sklearn.utils.fixes import delayed instead of joblib delayed. The following files contains imports to joblib.delayed:"
-    echo "$joblib_import"
+joblib_delayed_import="$(git grep -l -A 10 -E "joblib import.+delayed" -- "*.py" ":!sklearn/utils/_joblib.py" ":!sklearn/utils/parallel.py")"
+if [ ! -z "$joblib_delayed_import" ]; then
+    echo "Use from sklearn.utils.parallel import delayed instead of joblib delayed. The following files contains imports to joblib.delayed:"
+    echo "$joblib_delayed_import"
+    exit 1
+fi
+joblib_Parallel_import="$(git grep -l -A 10 -E "joblib import.+Parallel" -- "*.py" ":!sklearn/utils/_joblib.py" ":!sklearn/utils/parallel.py")"
+if [ ! -z "$joblib_Parallel_import" ]; then
+    echo "Use from sklearn.utils.parallel import Parallel instead of joblib Parallel. The following files contains imports to joblib.Parallel:"
+    echo "$joblib_Parallel_import"
     exit 1
 fi
diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index d55becb0c512a..b1a50f65f0f7b 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -1666,9 +1666,16 @@ Utilities from joblib:
    :toctree: generated/
    :template: function.rst
 
+   utils.parallel.delayed
    utils.parallel_backend
    utils.register_parallel_backend
 
+.. autosummary::
+   :toctree: generated/
+   :template: class.rst
+
+   utils.parallel.Parallel
+
 
 Recently deprecated
 ===================
diff --git a/doc/whats_new/v1.2.rst b/doc/whats_new/v1.2.rst
index 3bc338e68f5de..0189ae36ba1aa 100644
--- a/doc/whats_new/v1.2.rst
+++ b/doc/whats_new/v1.2.rst
@@ -9,6 +9,16 @@ Version 1.2.1
 
 **In Development**
 
+Changes impacting all modules
+-----------------------------
+
+- |Fix| Fix a bug where the current configuration was ignored in estimators using
+  `n_jobs > 1`. This bug was triggered for tasks dispatched by the auxillary
+  thread of `joblib` as :func:`sklearn.get_config` used to access an empty thread
+  local configuration instead of the configuration visible from the thread where
+  `joblib.Parallel` was first called.
+  :pr:`25363` by :user:`Guillaume Lemaitre <glemaitre>`.
+
 Changed models
 --------------
 
@@ -139,6 +149,13 @@ Changelog
   boolean. The type is maintained, instead of converting to `float64.`
   :pr:`25147` by :user:`Tim Head <betatim>`.
 
+- |API| :func:`utils.fixes.delayed` is deprecated in 1.2.1 and will be removed
+  in 1.5. Instead, import :func:`utils.parallel.delayed` and use it in
+  conjunction with the newly introduced :func:`utils.parallel.Parallel`
+  to ensure proper propagation of the scikit-learn configuration to
+  the workers.
+  :pr:`25363` by :user:`Guillaume Lemaitre <glemaitre>`.
+
 .. _changes_1_2:
 
 Version 1.2.0
diff --git a/sklearn/calibration.py b/sklearn/calibration.py
index 8b3e39e31f3bb..2c4a33616d22c 100644
--- a/sklearn/calibration.py
+++ b/sklearn/calibration.py
@@ -14,7 +14,6 @@
 
 from math import log
 import numpy as np
-from joblib import Parallel
 
 from scipy.special import expit
 from scipy.special import xlogy
@@ -36,7 +35,7 @@
 )
 
 from .utils.multiclass import check_classification_targets
-from .utils.fixes import delayed
+from .utils.parallel import delayed, Parallel
 from .utils._param_validation import StrOptions, HasMethods, Hidden
 from .utils.validation import (
     _check_fit_params,
diff --git a/sklearn/cluster/_mean_shift.py b/sklearn/cluster/_mean_shift.py
index 29723ad81d2d0..8a60bf770c958 100644
--- a/sklearn/cluster/_mean_shift.py
+++ b/sklearn/cluster/_mean_shift.py
@@ -16,13 +16,12 @@
 
 import numpy as np
 import warnings
-from joblib import Parallel
 from numbers import Integral, Real
 
 from collections import defaultdict
 from ..utils._param_validation import Interval
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils import check_random_state, gen_batches, check_array
 from ..base import BaseEstimator, ClusterMixin
 from ..neighbors import NearestNeighbors
diff --git a/sklearn/compose/_column_transformer.py b/sklearn/compose/_column_transformer.py
index ba54441e2b63e..aabe846ea174a 100644
--- a/sklearn/compose/_column_transformer.py
+++ b/sklearn/compose/_column_transformer.py
@@ -11,7 +11,6 @@
 
 import numpy as np
 from scipy import sparse
-from joblib import Parallel
 
 from ..base import clone, TransformerMixin
 from ..utils._estimator_html_repr import _VisualBlock
@@ -24,7 +23,7 @@
 from ..utils import check_pandas_support
 from ..utils.metaestimators import _BaseComposition
 from ..utils.validation import check_array, check_is_fitted, _check_feature_names_in
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 __all__ = ["ColumnTransformer", "make_column_transformer", "make_column_selector"]
diff --git a/sklearn/covariance/_graph_lasso.py b/sklearn/covariance/_graph_lasso.py
index 6b6116ecce040..dfbb7e75753c5 100644
--- a/sklearn/covariance/_graph_lasso.py
+++ b/sklearn/covariance/_graph_lasso.py
@@ -13,7 +13,6 @@
 from numbers import Integral, Real
 import numpy as np
 from scipy import linalg
-from joblib import Parallel
 
 from . import empirical_covariance, EmpiricalCovariance, log_likelihood
 
@@ -23,7 +22,7 @@
     check_random_state,
     check_scalar,
 )
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import Interval, StrOptions
 
 # mypy error: Module 'sklearn.linear_model' has no attribute '_cd_fast'
diff --git a/sklearn/decomposition/_dict_learning.py b/sklearn/decomposition/_dict_learning.py
index f734f7361944b..98e1e77742de2 100644
--- a/sklearn/decomposition/_dict_learning.py
+++ b/sklearn/decomposition/_dict_learning.py
@@ -13,7 +13,7 @@
 
 import numpy as np
 from scipy import linalg
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ..base import BaseEstimator, TransformerMixin, ClassNamePrefixFeaturesOutMixin
 from ..utils import check_array, check_random_state, gen_even_slices, gen_batches
@@ -21,7 +21,7 @@
 from ..utils._param_validation import Hidden, Interval, StrOptions
 from ..utils.extmath import randomized_svd, row_norms, svd_flip
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..linear_model import Lasso, orthogonal_mp_gram, LassoLars, Lars
 
 
diff --git a/sklearn/decomposition/_lda.py b/sklearn/decomposition/_lda.py
index d187611251eda..b7ef0af8eafd9 100644
--- a/sklearn/decomposition/_lda.py
+++ b/sklearn/decomposition/_lda.py
@@ -15,13 +15,13 @@
 import numpy as np
 import scipy.sparse as sp
 from scipy.special import gammaln, logsumexp
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ..base import BaseEstimator, TransformerMixin, ClassNamePrefixFeaturesOutMixin
 from ..utils import check_random_state, gen_batches, gen_even_slices
 from ..utils.validation import check_non_negative
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import Interval, StrOptions
 
 from ._online_lda_fast import (
diff --git a/sklearn/decomposition/tests/test_dict_learning.py b/sklearn/decomposition/tests/test_dict_learning.py
index 16a695d1189ab..7c383390f5b60 100644
--- a/sklearn/decomposition/tests/test_dict_learning.py
+++ b/sklearn/decomposition/tests/test_dict_learning.py
@@ -5,8 +5,6 @@
 from functools import partial
 import itertools
 
-from joblib import Parallel
-
 import sklearn
 
 from sklearn.base import clone
@@ -14,6 +12,7 @@
 from sklearn.exceptions import ConvergenceWarning
 
 from sklearn.utils import check_array
+from sklearn.utils.parallel import Parallel
 
 from sklearn.utils._testing import assert_allclose
 from sklearn.utils._testing import assert_array_almost_equal
diff --git a/sklearn/ensemble/_bagging.py b/sklearn/ensemble/_bagging.py
index fbe54a8afb530..4586e55a59f97 100644
--- a/sklearn/ensemble/_bagging.py
+++ b/sklearn/ensemble/_bagging.py
@@ -12,8 +12,6 @@
 from warnings import warn
 from functools import partial
 
-from joblib import Parallel
-
 from ._base import BaseEnsemble, _partition_estimators
 from ..base import ClassifierMixin, RegressorMixin
 from ..metrics import r2_score, accuracy_score
@@ -25,7 +23,7 @@
 from ..utils.random import sample_without_replacement
 from ..utils._param_validation import Interval, HasMethods, StrOptions
 from ..utils.validation import has_fit_parameter, check_is_fitted, _check_sample_weight
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 __all__ = ["BaggingClassifier", "BaggingRegressor"]
diff --git a/sklearn/ensemble/_forest.py b/sklearn/ensemble/_forest.py
index b13315a5c00a7..69f48e6344ce7 100644
--- a/sklearn/ensemble/_forest.py
+++ b/sklearn/ensemble/_forest.py
@@ -48,7 +48,6 @@ class calls the ``fit`` method of each sub-estimator on random samples
 import numpy as np
 from scipy.sparse import issparse
 from scipy.sparse import hstack as sparse_hstack
-from joblib import Parallel
 
 from ..base import is_classifier
 from ..base import ClassifierMixin, MultiOutputMixin, RegressorMixin, TransformerMixin
@@ -66,7 +65,7 @@ class calls the ``fit`` method of each sub-estimator on random samples
 from ..utils import check_random_state, compute_sample_weight
 from ..exceptions import DataConversionWarning
 from ._base import BaseEnsemble, _partition_estimators
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils.multiclass import check_classification_targets, type_of_target
 from ..utils.validation import (
     check_is_fitted,
diff --git a/sklearn/ensemble/_stacking.py b/sklearn/ensemble/_stacking.py
index 2e3d1b6db5798..e7468ddb5ac22 100644
--- a/sklearn/ensemble/_stacking.py
+++ b/sklearn/ensemble/_stacking.py
@@ -8,7 +8,6 @@
 from numbers import Integral
 
 import numpy as np
-from joblib import Parallel
 import scipy.sparse as sparse
 
 from ..base import clone
@@ -33,7 +32,7 @@
 from ..utils.metaestimators import available_if
 from ..utils.validation import check_is_fitted
 from ..utils.validation import column_or_1d
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import HasMethods, StrOptions
 from ..utils.validation import _check_feature_names_in
 
diff --git a/sklearn/ensemble/_voting.py b/sklearn/ensemble/_voting.py
index 2e1e27b3b3de9..97db90fc0c172 100644
--- a/sklearn/ensemble/_voting.py
+++ b/sklearn/ensemble/_voting.py
@@ -18,8 +18,6 @@
 
 import numpy as np
 
-from joblib import Parallel
-
 from ..base import ClassifierMixin
 from ..base import RegressorMixin
 from ..base import TransformerMixin
@@ -36,7 +34,7 @@
 from ..utils._param_validation import StrOptions
 from ..exceptions import NotFittedError
 from ..utils._estimator_html_repr import _VisualBlock
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 class _BaseVoting(TransformerMixin, _BaseHeterogeneousEnsemble):
diff --git a/sklearn/ensemble/tests/test_forest.py b/sklearn/ensemble/tests/test_forest.py
index 088b0f12d5cc1..aebc5ea87d52b 100644
--- a/sklearn/ensemble/tests/test_forest.py
+++ b/sklearn/ensemble/tests/test_forest.py
@@ -17,16 +17,15 @@
 from typing import Dict, Any
 
 import numpy as np
-from joblib import Parallel
 from scipy.sparse import csr_matrix
 from scipy.sparse import csc_matrix
 from scipy.sparse import coo_matrix
 from scipy.special import comb
 
-import pytest
-
 import joblib
 
+import pytest
+
 import sklearn
 from sklearn.dummy import DummyRegressor
 from sklearn.metrics import mean_poisson_deviance
@@ -55,6 +54,7 @@
 >>>>>>> c3fca81536 (FIX Support read-only sparse datasets for `Tree`-based estimators (#25341))
 from sklearn.model_selection import GridSearchCV
 from sklearn.svm import LinearSVC
+from sklearn.utils.parallel import Parallel
 from sklearn.utils.validation import check_random_state
 
 from sklearn.metrics import mean_squared_error
diff --git a/sklearn/feature_selection/_rfe.py b/sklearn/feature_selection/_rfe.py
index a025fe7c36490..d105ba1ae3567 100644
--- a/sklearn/feature_selection/_rfe.py
+++ b/sklearn/feature_selection/_rfe.py
@@ -8,7 +8,7 @@
 
 import numpy as np
 from numbers import Integral, Real
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 
 from ..utils.metaestimators import available_if
@@ -16,7 +16,7 @@
 from ..utils._param_validation import HasMethods, Interval
 from ..utils._tags import _safe_tags
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..base import BaseEstimator
 from ..base import MetaEstimatorMixin
 from ..base import clone
diff --git a/sklearn/inspection/_permutation_importance.py b/sklearn/inspection/_permutation_importance.py
index 63ab4f69968d8..a418cb34b3540 100644
--- a/sklearn/inspection/_permutation_importance.py
+++ b/sklearn/inspection/_permutation_importance.py
@@ -1,7 +1,6 @@
 """Permutation importance for estimators."""
 import numbers
 import numpy as np
-from joblib import Parallel
 
 from ..ensemble._bagging import _generate_indices
 from ..metrics import check_scoring
@@ -10,7 +9,7 @@
 from ..utils import Bunch, _safe_indexing
 from ..utils import check_random_state
 from ..utils import check_array
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 def _weights_scorer(scorer, estimator, X, y, sample_weight):
diff --git a/sklearn/inspection/_plot/partial_dependence.py b/sklearn/inspection/_plot/partial_dependence.py
index e3392eeb911b1..bba8e0dea826f 100644
--- a/sklearn/inspection/_plot/partial_dependence.py
+++ b/sklearn/inspection/_plot/partial_dependence.py
@@ -6,7 +6,6 @@
 import numpy as np
 from scipy import sparse
 from scipy.stats.mstats import mquantiles
-from joblib import Parallel
 
 from .. import partial_dependence
 from .._pd_utils import _check_feature_names, _get_feature_index
@@ -16,7 +15,7 @@
 from ...utils import check_matplotlib_support  # noqa
 from ...utils import check_random_state
 from ...utils import _safe_indexing
-from ...utils.fixes import delayed
+from ...utils.parallel import delayed, Parallel
 from ...utils._encode import _unique
 
 
diff --git a/sklearn/linear_model/_base.py b/sklearn/linear_model/_base.py
index a3ac37257a98b..987ae57c12250 100644
--- a/sklearn/linear_model/_base.py
+++ b/sklearn/linear_model/_base.py
@@ -25,7 +25,6 @@
 from scipy import sparse
 from scipy.sparse.linalg import lsqr
 from scipy.special import expit
-from joblib import Parallel
 from numbers import Integral
 
 from ..base import BaseEstimator, ClassifierMixin, RegressorMixin, MultiOutputMixin
@@ -40,7 +39,7 @@
 from ..utils._seq_dataset import ArrayDataset32, CSRDataset32
 from ..utils._seq_dataset import ArrayDataset64, CSRDataset64
 from ..utils.validation import check_is_fitted, _check_sample_weight
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 # TODO: bayesian_ridge_regression and bayesian_regression_ard
 # should be squashed into its respective objects.
diff --git a/sklearn/linear_model/_coordinate_descent.py b/sklearn/linear_model/_coordinate_descent.py
index 67fffac39d466..c1783be1ae45f 100644
--- a/sklearn/linear_model/_coordinate_descent.py
+++ b/sklearn/linear_model/_coordinate_descent.py
@@ -14,7 +14,7 @@
 
 import numpy as np
 from scipy import sparse
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ._base import LinearModel, _pre_fit
 from ..base import RegressorMixin, MultiOutputMixin
@@ -30,7 +30,7 @@
     check_is_fitted,
     column_or_1d,
 )
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 # mypy error: Module 'sklearn.linear_model' has no attribute '_cd_fast'
 from . import _cd_fast as cd_fast  # type: ignore
diff --git a/sklearn/linear_model/_least_angle.py b/sklearn/linear_model/_least_angle.py
index f3b3ba33517b8..7ed7b27811ec6 100644
--- a/sklearn/linear_model/_least_angle.py
+++ b/sklearn/linear_model/_least_angle.py
@@ -16,7 +16,6 @@
 import numpy as np
 from scipy import linalg, interpolate
 from scipy.linalg.lapack import get_lapack_funcs
-from joblib import Parallel
 
 from ._base import LinearModel, LinearRegression
 from ._base import _deprecate_normalize, _preprocess_data
@@ -28,7 +27,7 @@
 from ..utils._param_validation import Hidden, Interval, StrOptions
 from ..model_selection import check_cv
 from ..exceptions import ConvergenceWarning
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 SOLVE_TRIANGULAR_ARGS = {"check_finite": False}
 
diff --git a/sklearn/linear_model/_logistic.py b/sklearn/linear_model/_logistic.py
index 42f0ffb56d8e3..0d0da3983c664 100644
--- a/sklearn/linear_model/_logistic.py
+++ b/sklearn/linear_model/_logistic.py
@@ -16,7 +16,7 @@
 
 import numpy as np
 from scipy import optimize
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from sklearn.metrics import get_scorer_names
 
@@ -34,7 +34,7 @@
 from ..utils.optimize import _newton_cg, _check_optimize_result
 from ..utils.validation import check_is_fitted, _check_sample_weight
 from ..utils.multiclass import check_classification_targets
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import StrOptions, Interval
 from ..model_selection import check_cv
 from ..metrics import get_scorer
diff --git a/sklearn/linear_model/_omp.py b/sklearn/linear_model/_omp.py
index 819cfbfb21adc..f0bd04568c473 100644
--- a/sklearn/linear_model/_omp.py
+++ b/sklearn/linear_model/_omp.py
@@ -12,12 +12,11 @@
 import numpy as np
 from scipy import linalg
 from scipy.linalg.lapack import get_lapack_funcs
-from joblib import Parallel
 
 from ._base import LinearModel, _pre_fit, _deprecate_normalize
 from ..base import RegressorMixin, MultiOutputMixin
 from ..utils import as_float_array, check_array
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import Hidden, Interval, StrOptions
 from ..model_selection import check_cv
 
diff --git a/sklearn/linear_model/_stochastic_gradient.py b/sklearn/linear_model/_stochastic_gradient.py
index baa4361cac9ef..1361ef6a1c609 100644
--- a/sklearn/linear_model/_stochastic_gradient.py
+++ b/sklearn/linear_model/_stochastic_gradient.py
@@ -12,8 +12,6 @@
 from abc import ABCMeta, abstractmethod
 from numbers import Integral, Real
 
-from joblib import Parallel
-
 from ..base import clone, is_classifier
 from ._base import LinearClassifierMixin, SparseCoefMixin
 from ._base import make_dataset
@@ -26,7 +24,7 @@
 from ..utils._param_validation import Interval
 from ..utils._param_validation import StrOptions
 from ..utils._param_validation import Hidden
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..exceptions import ConvergenceWarning
 from ..model_selection import StratifiedShuffleSplit, ShuffleSplit
 
diff --git a/sklearn/linear_model/_theil_sen.py b/sklearn/linear_model/_theil_sen.py
index ab9c883add0c6..67d6ca532a8ab 100644
--- a/sklearn/linear_model/_theil_sen.py
+++ b/sklearn/linear_model/_theil_sen.py
@@ -15,13 +15,13 @@
 from scipy import linalg
 from scipy.special import binom
 from scipy.linalg.lapack import get_lapack_funcs
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ._base import LinearModel
 from ..base import RegressorMixin
 from ..utils import check_random_state
 from ..utils._param_validation import Interval
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..exceptions import ConvergenceWarning
 
 _EPSILON = np.finfo(np.double).eps
diff --git a/sklearn/manifold/_mds.py b/sklearn/manifold/_mds.py
index bfa4c6160d9ce..d6f99c84f55f1 100644
--- a/sklearn/manifold/_mds.py
+++ b/sklearn/manifold/_mds.py
@@ -8,7 +8,7 @@
 from numbers import Integral, Real
 
 import numpy as np
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 import warnings
 
@@ -17,7 +17,7 @@
 from ..utils import check_random_state, check_array, check_symmetric
 from ..isotonic import IsotonicRegression
 from ..utils._param_validation import Interval, StrOptions, Hidden
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 def _smacof_single(
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
index b34722dc25df7..3d01d5eeaf12d 100644
--- a/sklearn/metrics/pairwise.py
+++ b/sklearn/metrics/pairwise.py
@@ -15,7 +15,7 @@
 from scipy.spatial import distance
 from scipy.sparse import csr_matrix
 from scipy.sparse import issparse
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from .. import config_context
 from ..utils.validation import _num_samples
@@ -27,7 +27,7 @@
 from ..utils.extmath import row_norms, safe_sparse_dot
 from ..preprocessing import normalize
 from ..utils._mask import _get_mask
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils.fixes import sp_version, parse_version
 
 from ._pairwise_distances_reduction import ArgKmin
diff --git a/sklearn/model_selection/_search.py b/sklearn/model_selection/_search.py
index 14ef0d9651f2e..636a1429bd21b 100644
--- a/sklearn/model_selection/_search.py
+++ b/sklearn/model_selection/_search.py
@@ -33,13 +33,12 @@
 from ._validation import _normalize_score_results
 from ._validation import _warn_or_raise_about_fit_failures
 from ..exceptions import NotFittedError
-from joblib import Parallel
 from ..utils import check_random_state
 from ..utils.random import sample_without_replacement
 from ..utils._tags import _safe_tags
 from ..utils.validation import indexable, check_is_fitted, _check_fit_params
 from ..utils.metaestimators import available_if
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..metrics._scorer import _check_multimetric_scoring
 from ..metrics import check_scoring
 
diff --git a/sklearn/model_selection/_validation.py b/sklearn/model_selection/_validation.py
index 1a13b770cd1c5..8a626fe1ce1f3 100644
--- a/sklearn/model_selection/_validation.py
+++ b/sklearn/model_selection/_validation.py
@@ -21,13 +21,13 @@
 
 import numpy as np
 import scipy.sparse as sp
-from joblib import Parallel, logger
+from joblib import logger
 
 from ..base import is_classifier, clone
 from ..utils import indexable, check_random_state, _safe_indexing
 from ..utils.validation import _check_fit_params
 from ..utils.validation import _num_samples
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils.metaestimators import _safe_split
 from ..metrics import check_scoring
 from ..metrics._scorer import _check_multimetric_scoring, _MultimetricScorer
diff --git a/sklearn/multiclass.py b/sklearn/multiclass.py
index 318066391a638..863435e5c7a1f 100644
--- a/sklearn/multiclass.py
+++ b/sklearn/multiclass.py
@@ -56,9 +56,7 @@
     _ovr_decision_function,
 )
 from .utils.metaestimators import _safe_split, available_if
-from .utils.fixes import delayed
-
-from joblib import Parallel
+from .utils.parallel import delayed, Parallel
 
 __all__ = [
     "OneVsRestClassifier",
diff --git a/sklearn/multioutput.py b/sklearn/multioutput.py
index ba3ddf9572232..4b7015dd40ece 100644
--- a/sklearn/multioutput.py
+++ b/sklearn/multioutput.py
@@ -17,7 +17,6 @@
 
 import numpy as np
 import scipy.sparse as sp
-from joblib import Parallel
 
 from abc import ABCMeta, abstractmethod
 from .base import BaseEstimator, clone, MetaEstimatorMixin
@@ -31,7 +30,7 @@
     has_fit_parameter,
     _check_fit_params,
 )
-from .utils.fixes import delayed
+from .utils.parallel import delayed, Parallel
 from .utils._param_validation import HasMethods, StrOptions
 
 __all__ = [
diff --git a/sklearn/neighbors/_base.py b/sklearn/neighbors/_base.py
index 3b01824a3a73a..2e97bab4a4f8d 100644
--- a/sklearn/neighbors/_base.py
+++ b/sklearn/neighbors/_base.py
@@ -16,7 +16,7 @@
 
 import numpy as np
 from scipy.sparse import csr_matrix, issparse
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ._ball_tree import BallTree
 from ._kd_tree import KDTree
@@ -37,8 +37,8 @@
 from ..utils.validation import check_is_fitted
 from ..utils.validation import check_non_negative
 from ..utils._param_validation import Interval, StrOptions
-from ..utils.fixes import delayed, sp_version
-from ..utils.fixes import parse_version
+from ..utils.parallel import delayed, Parallel
+from ..utils.fixes import parse_version, sp_version
 from ..exceptions import DataConversionWarning, EfficiencyWarning
 
 VALID_METRICS = dict(
diff --git a/sklearn/neighbors/tests/test_kd_tree.py b/sklearn/neighbors/tests/test_kd_tree.py
index d8d9437636d1d..525c15436e24c 100644
--- a/sklearn/neighbors/tests/test_kd_tree.py
+++ b/sklearn/neighbors/tests/test_kd_tree.py
@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
-from joblib import Parallel
-from sklearn.utils.fixes import delayed
+from sklearn.utils.parallel import delayed, Parallel
 
 from sklearn.neighbors._kd_tree import KDTree
 
diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index b3a4d180a4c68..50f8f11fa212e 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -14,7 +14,6 @@
 
 import numpy as np
 from scipy import sparse
-from joblib import Parallel
 
 from .base import clone, TransformerMixin
 from .preprocessing import FunctionTransformer
@@ -29,7 +28,7 @@
 from .utils.validation import check_is_fitted
 from .utils import check_pandas_support
 from .utils._set_output import _safe_set_output, _get_output_config
-from .utils.fixes import delayed
+from .utils.parallel import delayed, Parallel
 from .exceptions import NotFittedError
 
 from .utils.metaestimators import _BaseComposition
diff --git a/sklearn/tests/test_config.py b/sklearn/tests/test_config.py
index a0b8f29662b69..bcc4c233e7ea3 100644
--- a/sklearn/tests/test_config.py
+++ b/sklearn/tests/test_config.py
@@ -1,11 +1,10 @@
 import time
 from concurrent.futures import ThreadPoolExecutor
 
-from joblib import Parallel
 import pytest
 
 from sklearn import get_config, set_config, config_context
-from sklearn.utils.fixes import delayed
+from sklearn.utils.parallel import delayed, Parallel
 
 
 def test_config_context():
@@ -120,15 +119,15 @@ def test_config_threadsafe_joblib(backend):
     should be the same as the value passed to the function. In other words,
     it is not influenced by the other job setting assume_finite to True.
     """
-    assume_finites = [False, True]
-    sleep_durations = [0.1, 0.2]
+    assume_finites = [False, True, False, True]
+    sleep_durations = [0.1, 0.2, 0.1, 0.2]
 
     items = Parallel(backend=backend, n_jobs=2)(
         delayed(set_assume_finite)(assume_finite, sleep_dur)
         for assume_finite, sleep_dur in zip(assume_finites, sleep_durations)
     )
 
-    assert items == [False, True]
+    assert items == [False, True, False, True]
 
 
 def test_config_threadsafe():
@@ -136,8 +135,8 @@ def test_config_threadsafe():
     between threads. Same test as `test_config_threadsafe_joblib` but with
     `ThreadPoolExecutor`."""
 
-    assume_finites = [False, True]
-    sleep_durations = [0.1, 0.2]
+    assume_finites = [False, True, False, True]
+    sleep_durations = [0.1, 0.2, 0.1, 0.2]
 
     with ThreadPoolExecutor(max_workers=2) as e:
         items = [
@@ -145,4 +144,4 @@ def test_config_threadsafe():
             for output in e.map(set_assume_finite, assume_finites, sleep_durations)
         ]
 
-    assert items == [False, True]
+    assert items == [False, True, False, True]
diff --git a/sklearn/utils/fixes.py b/sklearn/utils/fixes.py
index 53fe56ea68144..37a25ff96ba00 100644
--- a/sklearn/utils/fixes.py
+++ b/sklearn/utils/fixes.py
@@ -10,9 +10,7 @@
 #
 # License: BSD 3 clause
 
-from functools import update_wrapper
 from importlib import resources
-import functools
 import sys
 
 import sklearn
@@ -20,7 +18,8 @@
 import scipy
 import scipy.stats
 import threadpoolctl
-from .._config import config_context, get_config
+
+from .deprecation import deprecated
 from ..externals._packaging.version import parse as parse_version
 
 
@@ -106,30 +105,6 @@ def _eigh(*args, **kwargs):
         return scipy.linalg.eigh(*args, eigvals=eigvals, **kwargs)
 
 
-# remove when https://github.com/joblib/joblib/issues/1071 is fixed
-def delayed(function):
-    """Decorator used to capture the arguments of a function."""
-
-    @functools.wraps(function)
-    def delayed_function(*args, **kwargs):
-        return _FuncWrapper(function), args, kwargs
-
-    return delayed_function
-
-
-class _FuncWrapper:
-    """ "Load the global configuration before calling the function."""
-
-    def __init__(self, function):
-        self.function = function
-        self.config = get_config()
-        update_wrapper(self, self.function)
-
-    def __call__(self, *args, **kwargs):
-        with config_context(**self.config):
-            return self.function(*args, **kwargs)
-
-
 # Rename the `method` kwarg to `interpolation` for NumPy < 1.22, because
 # `interpolation` kwarg was deprecated in favor of `method` in NumPy >= 1.22.
 def _percentile(a, q, *, method="linear", **kwargs):
@@ -178,6 +153,16 @@ def threadpool_info():
 threadpool_info.__doc__ = threadpoolctl.threadpool_info.__doc__
 
 
+@deprecated(
+    "The function `delayed` has been moved from `sklearn.utils.fixes` to "
+    "`sklearn.utils.parallel`. This import path will be removed in 1.5."
+)
+def delayed(function):
+    from sklearn.utils.parallel import delayed
+
+    return delayed(function)
+
+
 # TODO: Remove when SciPy 1.11 is the minimum supported version
 def _mode(a, axis=0):
     if sp_version >= parse_version("1.9.0"):
diff --git a/sklearn/utils/parallel.py b/sklearn/utils/parallel.py
new file mode 100644
index 0000000000000..48a31ee93d8a0
--- /dev/null
+++ b/sklearn/utils/parallel.py
@@ -0,0 +1,123 @@
+"""Module that customize joblib tools for scikit-learn usage."""
+
+import functools
+import warnings
+from functools import update_wrapper
+
+import joblib
+
+from .._config import config_context, get_config
+
+
+def _with_config(delayed_func, config):
+    """Helper function that intends to attach a config to a delayed function."""
+    if hasattr(delayed_func, "with_config"):
+        return delayed_func.with_config(config)
+    else:
+        warnings.warn(
+            "`sklearn.utils.parallel.Parallel` needs to be used in "
+            "conjunction with `sklearn.utils.parallel.delayed` instead of "
+            "`joblib.delayed` to correctly propagate the scikit-learn "
+            "configuration to the joblib workers.",
+            UserWarning,
+        )
+        return delayed_func
+
+
+class Parallel(joblib.Parallel):
+    """Tweak of :class:`joblib.Parallel` that propagates the scikit-learn configuration.
+
+    This subclass of :class:`joblib.Parallel` ensures that the active configuration
+    (thread-local) of scikit-learn is propagated to the parallel workers for the
+    duration of the execution of the parallel tasks.
+
+    The API does not change and you can refer to :class:`joblib.Parallel`
+    documentation for more details.
+
+    .. versionadded:: 1.3
+    """
+
+    def __call__(self, iterable):
+        """Dispatch the tasks and return the results.
+
+        Parameters
+        ----------
+        iterable : iterable
+            Iterable containing tuples of (delayed_function, args, kwargs) that should
+            be consumed.
+
+        Returns
+        -------
+        results : list
+            List of results of the tasks.
+        """
+        # Capture the thread-local scikit-learn configuration at the time
+        # Parallel.__call__ is issued since the tasks can be dispatched
+        # in a different thread depending on the backend and on the value of
+        # pre_dispatch and n_jobs.
+        config = get_config()
+        iterable_with_config = (
+            (_with_config(delayed_func, config), args, kwargs)
+            for delayed_func, args, kwargs in iterable
+        )
+        return super().__call__(iterable_with_config)
+
+
+# remove when https://github.com/joblib/joblib/issues/1071 is fixed
+def delayed(function):
+    """Decorator used to capture the arguments of a function.
+
+    This alternative to `joblib.delayed` is meant to be used in conjunction
+    with `sklearn.utils.parallel.Parallel`. The latter captures the the scikit-
+    learn configuration by calling `sklearn.get_config()` in the current
+    thread, prior to dispatching the first task. The captured configuration is
+    then propagated and enabled for the duration of the execution of the
+    delayed function in the joblib workers.
+
+    .. versionchanged:: 1.3
+       `delayed` was moved from `sklearn.utils.fixes` to `sklearn.utils.parallel`
+       in scikit-learn 1.3.
+
+    Parameters
+    ----------
+    function : callable
+        The function to be delayed.
+
+    Returns
+    -------
+    output: tuple
+        Tuple containing the delayed function, the positional arguments, and the
+        keyword arguments.
+    """
+
+    @functools.wraps(function)
+    def delayed_function(*args, **kwargs):
+        return _FuncWrapper(function), args, kwargs
+
+    return delayed_function
+
+
+class _FuncWrapper:
+    """Load the global configuration before calling the function."""
+
+    def __init__(self, function):
+        self.function = function
+        update_wrapper(self, self.function)
+
+    def with_config(self, config):
+        self.config = config
+        return self
+
+    def __call__(self, *args, **kwargs):
+        config = getattr(self, "config", None)
+        if config is None:
+            warnings.warn(
+                "`sklearn.utils.parallel.delayed` should be used with "
+                "`sklearn.utils.parallel.Parallel` to make it possible to propagate "
+                "the scikit-learn configuration of the current thread to the "
+                "joblib workers.",
+                UserWarning,
+            )
+            config = {}
+        with config_context(**config):
+            return self.function(*args, **kwargs)
diff --git a/sklearn/utils/tests/test_fixes.py b/sklearn/utils/tests/test_fixes.py
index 3566897da5efc..64db4006b5f1a 100644
--- a/sklearn/utils/tests/test_fixes.py
+++ b/sklearn/utils/tests/test_fixes.py
@@ -11,8 +11,7 @@
 
 from sklearn.utils._testing import assert_array_equal
 
-from sklearn.utils.fixes import _object_dtype_isnan
-from sklearn.utils.fixes import loguniform
+from sklearn.utils.fixes import _object_dtype_isnan, delayed, loguniform
 
 
 @pytest.mark.parametrize("dtype, val", ([object, 1], [object, "a"], [float, 1]))
@@ -46,3 +45,14 @@ def test_loguniform(low, high, base):
     assert loguniform(base**low, base**high).rvs(random_state=0) == loguniform(
         base**low, base**high
     ).rvs(random_state=0)
+
+
+def test_delayed_deprecation():
+    """Check that we issue the FutureWarning regarding the deprecation of delayed."""
+
+    def func(x):
+        return x
+
+    warn_msg = "The function `delayed` has been moved from `sklearn.utils.fixes`"
+    with pytest.warns(FutureWarning, match=warn_msg):
+        delayed(func)
diff --git a/sklearn/utils/tests/test_parallel.py b/sklearn/utils/tests/test_parallel.py
index dfecd7b464168..2f56c584300d1 100644
--- a/sklearn/utils/tests/test_parallel.py
+++ b/sklearn/utils/tests/test_parallel.py
@@ -1,10 +1,19 @@
-import pytest
-from joblib import Parallel
+import time
 
+import joblib
+import numpy as np
+import pytest
 from numpy.testing import assert_array_equal
 
-from sklearn._config import config_context, get_config
-from sklearn.utils.fixes import delayed
+from sklearn import config_context, get_config
+from sklearn.compose import make_column_transformer
+from sklearn.datasets import load_iris
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.model_selection import GridSearchCV
+from sklearn.pipeline import make_pipeline
+from sklearn.preprocessing import StandardScaler
+
+from sklearn.utils.parallel import delayed, Parallel
 
 
 def get_working_memory():
@@ -22,3 +31,71 @@ def test_configuration_passes_through_to_joblib(n_jobs, backend):
         )
 
     assert_array_equal(results, [123] * 2)
+
+
+def test_parallel_delayed_warnings():
+    """Informative warnings should be raised when mixing sklearn and joblib API"""
+    # We should issue a warning when one wants to use sklearn.utils.fixes.Parallel
+    # with joblib.delayed. The config will not be propagated to the workers.
+    warn_msg = "`sklearn.utils.parallel.Parallel` needs to be used in conjunction"
+    with pytest.warns(UserWarning, match=warn_msg) as records:
+        Parallel()(joblib.delayed(time.sleep)(0) for _ in range(10))
+    assert len(records) == 10
+
+    # We should issue a warning if one wants to use sklearn.utils.fixes.delayed with
+    # joblib.Parallel
+    warn_msg = (
+        "`sklearn.utils.parallel.delayed` should be used with "
+        "`sklearn.utils.parallel.Parallel` to make it possible to propagate"
+    )
+    with pytest.warns(UserWarning, match=warn_msg) as records:
+        joblib.Parallel()(delayed(time.sleep)(0) for _ in range(10))
+    assert len(records) == 10
+
+
+@pytest.mark.parametrize("n_jobs", [1, 2])
+def test_dispatch_config_parallel(n_jobs):
+    """Check that we properly dispatch the configuration in parallel processing.
+
+    Non-regression test for:
+    https://github.com/scikit-learn/scikit-learn/issues/25239
+    """
+    pd = pytest.importorskip("pandas")
+    iris = load_iris(as_frame=True)
+
+    class TransformerRequiredDataFrame(StandardScaler):
+        def fit(self, X, y=None):
+            assert isinstance(X, pd.DataFrame), "X should be a DataFrame"
+            return super().fit(X, y)
+
+        def transform(self, X, y=None):
+            assert isinstance(X, pd.DataFrame), "X should be a DataFrame"
+            return super().transform(X, y)
+
+    dropper = make_column_transformer(
+        ("drop", [0]),
+        remainder="passthrough",
+        n_jobs=n_jobs,
+    )
+    param_grid = {"randomforestclassifier__max_depth": [1, 2, 3]}
+    search_cv = GridSearchCV(
+        make_pipeline(
+            dropper,
+            TransformerRequiredDataFrame(),
+            RandomForestClassifier(n_estimators=5, n_jobs=n_jobs),
+        ),
+        param_grid,
+        cv=5,
+        n_jobs=n_jobs,
+        error_score="raise",  # this search should not fail
+    )
+
+    # make sure that `fit` would fail in case we don't request dataframe
+    with pytest.raises(AssertionError, match="X should be a DataFrame"):
+        search_cv.fit(iris.data, iris.target)
+
+    with config_context(transform_output="pandas"):
+        # we expect each intermediate steps to output a DataFrame
+        search_cv.fit(iris.data, iris.target)
+
+    assert not np.isnan(search_cv.cv_results_["mean_test_score"]).any()