diff --git a/README.md b/README.md
index d85947ecc1..88513bca5f 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@
 
 Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and
 scalable distributed training of machine learning (ML) models created with various ML frameworks
-such as PyTorch, TensorFlow, HuggingFace, Jax, DeepSpeed, XGBoost, PaddlePaddle and others.
+such as PyTorch, TensorFlow, HuggingFace, [JAX](https://jax.readthedocs.io/en/latest/), DeepSpeed, XGBoost, PaddlePaddle and others.
 
 You can run high-performance computing (HPC) tasks with the Training Operator and `MPIJob` since it
 supports running Message Passing Interface (MPI) on Kubernetes which is heavily used for HPC.
@@ -103,6 +103,7 @@ For a complete reference of the custom resource definitions, please refer to the
 - [XGBoost API Definition](pkg/apis/kubeflow.org/v1/xgboost_types.go)
 - [MPI API Definition](pkg/apis/kubeflow.org/v1/mpi_types.go)
 - [PaddlePaddle API Definition](pkg/apis/kubeflow.org/v1/paddlepaddle_types.go)
+- [JAX API Definition](pkg/apis/kubeflow.org/v1/jax_types.go)
 
 For details on the Training Operator custom resources APIs, refer to
 [the following API documentation](docs/api/kubeflow.org_v1_generated.asciidoc)
diff --git a/examples/jax/cpu-demo/demo.yaml b/examples/jax/cpu-demo/demo.yaml
index 85c99c9b18..bffd3cc16f 100644
--- a/examples/jax/cpu-demo/demo.yaml
+++ b/examples/jax/cpu-demo/demo.yaml
@@ -12,7 +12,7 @@ spec:
         spec:
           containers:
             - name: jax
-              image: docker.io/sandipanify/jaxgoogle:latest
+              image: docker.io/kubeflow/jaxjob-simple:latest
               command:
                 - "python3"
                 - "train.py"
diff --git a/pkg/controller.v1/jax/envvar_test.go b/pkg/controller.v1/jax/envvar_test.go
index e8155c5274..9920e89bbb 100644
--- a/pkg/controller.v1/jax/envvar_test.go
+++ b/pkg/controller.v1/jax/envvar_test.go
@@ -30,7 +30,7 @@ func TestSetPodEnv(t *testing.T) {
 						Spec: corev1.PodSpec{
 							Containers: []corev1.Container{{
 								Name:  "jax",
-								Image: "docker.io/sandipanify/jaxgoogle:latest",
+								Image: "docker.io/kubeflow/jaxjob-simple:latest",
 								Ports: []corev1.ContainerPort{{
 									Name:          kubeflowv1.JAXJobDefaultPortName,
 									ContainerPort: validPort,
diff --git a/pkg/webhooks/jax/jaxjob_webhook_test.go b/pkg/webhooks/jax/jaxjob_webhook_test.go
index ed3bd2bd1b..bfbc0eb29c 100644
--- a/pkg/webhooks/jax/jaxjob_webhook_test.go
+++ b/pkg/webhooks/jax/jaxjob_webhook_test.go
@@ -38,7 +38,7 @@ func TestValidateV1JAXJob(t *testing.T) {
 				Spec: corev1.PodSpec{
 					Containers: []corev1.Container{{
 						Name:  "jax",
-						Image: "docker.io/sandipanify/jaxgoogle:latest",
+						Image: "docker.io/kubeflow/jaxjob-simple:latest",
 						Ports: []corev1.ContainerPort{{
 							Name:          "jaxjob-port",
 							ContainerPort: 6666,
diff --git a/sdk/python/kubeflow/training/constants/constants.py b/sdk/python/kubeflow/training/constants/constants.py
index 0bb6fe495e..e745468736 100644
--- a/sdk/python/kubeflow/training/constants/constants.py
+++ b/sdk/python/kubeflow/training/constants/constants.py
@@ -144,7 +144,7 @@
 JAXJOB_PLURAL = "jaxjobs"
 JAXJOB_CONTAINER = "jax"
 JAXJOB_REPLICA_TYPES = REPLICA_TYPE_WORKER.lower()
-JAXJOB_BASE_IMAGE = "kubeflow/jaxjob-simple:latest"
+JAXJOB_BASE_IMAGE = "docker.io/kubeflow/jaxjob-simple:latest"
 
 # Dictionary to get plural, model, and container for each Job kind.
 JOB_PARAMETERS = {
diff --git a/sdk/python/test/e2e/test_e2e_jaxjob.py b/sdk/python/test/e2e/test_e2e_jaxjob.py
index cf350f1c11..6223c8a988 100644
--- a/sdk/python/test/e2e/test_e2e_jaxjob.py
+++ b/sdk/python/test/e2e/test_e2e_jaxjob.py
@@ -155,7 +155,7 @@ def generate_jaxjob(
 def generate_container() -> V1Container:
     return V1Container(
         name=CONTAINER_NAME,
-        image="docker.io/sandipanify/jaxgoogle:latest",
+        image="docker.io/kubeflow/jaxjob-simple:latest",
         command=["python", "train.py"],
         resources=V1ResourceRequirements(limits={"memory": "2Gi", "cpu": "0.8"}),
     )