diff --git a/docker/build_artifacts/sagemaker/python_service.py b/docker/build_artifacts/sagemaker/python_service.py
index fd9954cc..d4fbeeaa 100644
--- a/docker/build_artifacts/sagemaker/python_service.py
+++ b/docker/build_artifacts/sagemaker/python_service.py
@@ -26,7 +26,7 @@
 import tfs_utils
 
 SAGEMAKER_MULTI_MODEL_ENABLED = os.environ.get("SAGEMAKER_MULTI_MODEL", "false").lower() == "true"
-MODEL_DIR = "models" if SAGEMAKER_MULTI_MODEL_ENABLED else "model"
+MODEL_DIR = "" if SAGEMAKER_MULTI_MODEL_ENABLED else "model"
 INFERENCE_SCRIPT_PATH = f"/opt/ml/{MODEL_DIR}/code/inference.py"
 
 SAGEMAKER_BATCHING_ENABLED = os.environ.get("SAGEMAKER_TFS_ENABLE_BATCHING", "false").lower()
@@ -78,12 +78,15 @@ def __init__(self):
                 self._setup_channel(grpc_port)
 
         if os.path.exists(INFERENCE_SCRIPT_PATH):
+            log.info("Inference script found at path {}".format(INFERENCE_SCRIPT_PATH))
+            log.info("Inference script exists, importing handlers.")
             # Single-Model Mode & Multi-Model Mode both use one inference.py
             self._handler, self._input_handler, self._output_handler = self._import_handlers()
             self._handlers = self._make_handler(
                 self._handler, self._input_handler, self._output_handler
             )
         else:
+            log.info("Inference script does not exist, using default handlers.")
             self._handlers = default_handler
 
         self._tfs_enable_batching = SAGEMAKER_BATCHING_ENABLED == "true"
diff --git a/docker/build_artifacts/sagemaker/serve.py b/docker/build_artifacts/sagemaker/serve.py
index a31e3e62..29a577da 100644
--- a/docker/build_artifacts/sagemaker/serve.py
+++ b/docker/build_artifacts/sagemaker/serve.py
@@ -28,9 +28,8 @@
 JS_INVOCATIONS = "js_content tensorflowServing.invocations"
 GUNICORN_PING = "proxy_pass http://gunicorn_upstream/ping"
 GUNICORN_INVOCATIONS = "proxy_pass http://gunicorn_upstream/invocations"
-MULTI_MODEL = "s" if os.environ.get("SAGEMAKER_MULTI_MODEL", "False").lower() == "true" else ""
-MODEL_DIR = f"model{MULTI_MODEL}"
-CODE_DIR = "/opt/ml/{}/code".format(MODEL_DIR)
+MODEL_DIR = "" if os.environ.get("SAGEMAKER_MULTI_MODEL", "False").lower() == "true" else "model"
+CODE_DIR = f"/opt/ml/{MODEL_DIR}/code"
 PYTHON_LIB_PATH = os.path.join(CODE_DIR, "lib")
 REQUIREMENTS_PATH = os.path.join(CODE_DIR, "requirements.txt")
 INFERENCE_PATH = os.path.join(CODE_DIR, "inference.py")
@@ -242,7 +241,7 @@ def _download_scripts(self, bucket, prefix):
         paginator = client.get_paginator("list_objects")
         for result in paginator.paginate(Bucket=bucket, Delimiter="/", Prefix=prefix):
             for file in result.get("Contents", []):
-                destination = os.path.join(CODE_DIR, file.get("Key"))
+                destination = os.path.join(CODE_DIR, file.get("Key").split("/")[-1])
                 if not os.path.exists(os.path.dirname(destination)):
                     os.makedirs(os.path.dirname(destination))
                 resource.meta.client.download_file(bucket, file.get("Key"), destination)