diff --git a/tutorials/deployment/README.md b/tutorials/deployment/README.md
new file mode 100644
index 000000000..5f26631ab
--- /dev/null
+++ b/tutorials/deployment/README.md
@@ -0,0 +1,3 @@
+This directory contains scripts & instructions on deploying Curator in different environments.
+
+Since Curator primarily runs on Ray clusters please also refer to the [Ray documentation on deploying clusters](https://docs.ray.io/en/latest/cluster/getting-started.html) for more examples and guides on deploying Ray clusters.
diff --git a/tutorials/deployment/slurm/README.md b/tutorials/deployment/slurm/README.md
new file mode 100644
index 000000000..33e65f02a
--- /dev/null
+++ b/tutorials/deployment/slurm/README.md
@@ -0,0 +1,14 @@
+The ray-sbatch-job.sh script is an example script that can be adapted to be used for single and multi-node slurm deployments in clusters that support container images in allocations.
+
+It is recommneded to update the following variables/options before running in your own environment:
+- `CONTAINER_MOUNTS` - Specify the mounts needed for the job. If no mounts are needed remove the `--container-mounts` flag from the `srun` commands.
+- `IMAGE` - Update to use the latest Curator Image or any Image of choice
+- `RUN_COMMAND` - Point to a script/python file that executes the main curation workflow.
+- `SBATCH DIRECTIVES` - Set the relevant SBATCH directives in the file or pass as flags when submitting the job.
+
+All of the options above can be modified in the script or set as environment variables that override the defaults in the script. For example:
+```bash
+RUN_COMMAND="python curation_script.py" IMAGE="my/image" CONTAINER_MOUNTS="/path/to/dataset:/data-dir" sbatch --nodes=2 -J=my-curation-job -A=my-account ray-batch-job.sh
+```
+
+For slurm environments that do not support or use containers, the script can be modified to call `module load` and source a venv for every `srun` command instead of using a container.
diff --git a/tutorials/deployment/slurm/ray-sbatch-job.sh b/tutorials/deployment/slurm/ray-sbatch-job.sh
new file mode 100644
index 000000000..d9ca7fc52
--- /dev/null
+++ b/tutorials/deployment/slurm/ray-sbatch-job.sh
@@ -0,0 +1,138 @@
+#!/bin/bash
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+
+# USAGE: sbatch --{optional-flags} ray-sbatch-job.sh
+# EXAMPLE: RUN_SCRIPT="python curation_script.py" sbatch --time=00:30:00 --nodes=2 ray-sbatch-job.sh
+
+########################################################
+# SLURM Directives
+########################################################
+#SBATCH --exclusive
+#SBATCH --output=curator-%j.out
+
+# NOTE: Some commonly used options are commented out below, uncomment them if you need to set them or add your own
+# #SBATCH --job-name=curator-pipeline
+# #SBATCH --nodes=1
+# #SBATCH --time=02:00:00
+# #SBATCH --account=my_account
+# #SBATCH --partition=my_partition
+# #SBATCH --dependency=singleton
+
+
+set -ux
+
+
+########################################################
+# User knobs (override via env vars) or in the script
+########################################################
+: "${RUN_COMMAND:=python -c 'import ray; ray.init(); print(ray.cluster_resources())'}" # Change as needed
+
+# Ports
+: "${GCS_PORT:=6379}"          # Ray GCS (native) port
+: "${CLIENT_PORT:=10001}"      # Ray Client port (ray://)
+: "${DASH_PORT:=8265}"         # Dashboard port
+
+
+########################################################
+# Container specific variables
+########################################################
+: "${IMAGE:=nvcr.io/nvidia/nemo-curator:25.09}"
+: "${CONTAINER_MOUNTS:=}" # Set as needed
+
+
+########################################################
+# Ray setup variables
+########################################################
+NUM_CPUS_PER_NODE="${NUM_CPUS_PER_NODE:-$(srun --jobid ${JOB_ID} --nodes=1 bash -c "echo \${SLURM_CPUS_ON_NODE}")}"
+NUM_GPUS_PER_NODE="${NUM_GPUS_PER_NODE:-8}"
+
+
+JOB_ID=${SLURM_JOB_ID}
+# Getting the node names
+NODES=${NODES:-$(scontrol show hostnames $(sacct -j ${JOB_ID} -X --json | jq -r .jobs[0].nodes))}
+NODES=(${NODES})
+
+HEAD_NODE_NAME=${NODES[0]}
+HEAD_NODE_IP=$(srun --jobid ${JOB_ID} --nodes=1 --ntasks=1 -w "$HEAD_NODE_NAME" bash -c "hostname  --ip-address")
+
+RAY_GCS_ADDRESS=$HEAD_NODE_IP:$GCS_PORT
+RAY_CLIENT_ADDRESS=$HEAD_NODE_IP:$CLIENT_PORT
+export RAY_GCS_ADDRESS
+export RAY_CLIENT_ADDRESS
+export RAY_ADDRESS="ray://$RAY_CLIENT_ADDRESS"
+
+echo "RAY_ADDRESS: $RAY_ADDRESS"
+
+
+
+# number of nodes other than the head node
+NUM_WORKERS=$((${#NODES[@]} - 1))
+
+########################################################
+# Start ray on the head node
+########################################################
+srun \
+  --nodes=1 \
+  -w ${HEAD_NODE_NAME} \
+  --container-image=$IMAGE \
+  --container-mounts=$CONTAINER_MOUNTS \
+    bash -c "ray start \
+                --head \
+                --num-cpus ${NUM_CPUS_PER_NODE} \
+                --num-gpus ${NUM_GPUS_PER_NODE} \
+                --temp-dir /tmp/ray_${JOB_ID} \
+                --node-ip-address ${HEAD_NODE_IP} \
+                --port ${GCS_PORT} \
+                --disable-usage-stats \
+                --dashboard-host 0.0.0.0 \
+                --dashboard-port ${DASH_PORT} \
+                --ray-client-server-port ${CLIENT_PORT} \
+                --block" &
+sleep 10
+
+########################################################
+# Start ray on the worker nodes
+########################################################
+for ((i = 1; i <= NUM_WORKERS; i++)); do
+    NODE_I=${NODES[$i]}
+    echo "Initializing WORKER $i at $NODE_I"
+    srun \
+      --nodes=1 \
+      -w ${NODE_I} \
+      --container-image=$IMAGE \
+      --container-mounts=$CONTAINER_MOUNTS \
+        bash -c "ray start \
+                     --address ${RAY_GCS_ADDRESS} \
+                     --num-cpus ${NUM_CPUS_PER_NODE} \
+                     --num-gpus ${NUM_GPUS_PER_NODE} \
+                     --block;" &
+    sleep 1
+done
+sleep 10
+
+########################################################
+# Run the command
+########################################################
+echo "RUNNING COMMAND $RUN_COMMAND"
+
+srun \
+  --nodes=1 \
+  --overlap \
+  -w ${HEAD_NODE_NAME} \
+  --container-image=$IMAGE \
+  --container-mounts=$CONTAINER_MOUNTS \
+    bash -c "RAY_ADDRESS=$RAY_ADDRESS $RUN_COMMAND"