diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index e0e0ec2d76..b98b2adcf2 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -2,6 +2,11 @@
 CHANGELOG
 =========
 
+1.11.1dev
+=========
+
+* enhancement: Local Mode: add training environment variables for AWS region and job name
+
 1.11.0
 ======
 
diff --git a/src/sagemaker/local/image.py b/src/sagemaker/local/image.py
index edd0543b08..74a9e50c1b 100644
--- a/src/sagemaker/local/image.py
+++ b/src/sagemaker/local/image.py
@@ -34,9 +34,13 @@
 import sagemaker
 from sagemaker.utils import get_config_value
 
-CONTAINER_PREFIX = "algo"
+CONTAINER_PREFIX = 'algo'
 DOCKER_COMPOSE_FILENAME = 'docker-compose.yaml'
 
+# Environment variables to be set during training
+REGION_ENV_NAME = 'AWS_REGION'
+TRAINING_JOB_NAME_ENV_NAME = 'TRAINING_JOB_NAME'
+
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.WARNING)
 
@@ -102,7 +106,12 @@ def train(self, input_data_config, hyperparameters):
             self.write_config_files(host, hyperparameters, input_data_config)
             shutil.copytree(data_dir, os.path.join(self.container_root, host, 'input', 'data'))
 
-        compose_data = self._generate_compose_file('train', additional_volumes=volumes)
+        training_env_vars = {
+            REGION_ENV_NAME: self.sagemaker_session.boto_region_name,
+            TRAINING_JOB_NAME_ENV_NAME: json.loads(hyperparameters.get(sagemaker.model.JOB_NAME_PARAM_NAME)),
+        }
+        compose_data = self._generate_compose_file('train', additional_volumes=volumes,
+                                                   additional_env_vars=training_env_vars)
         compose_command = self._compose()
 
         _ecr_login_if_needed(self.sagemaker_session.boto_session, self.image)
@@ -149,7 +158,6 @@ def serve(self, model_dir, environment):
         logger.info('creating hosting dir in {}'.format(self.container_root))
 
         volumes = self._prepare_serving_volumes(model_dir)
-        env_vars = ['{}={}'.format(k, v) for k, v in environment.items()]
 
         # If the user script was passed as a file:// mount it to the container.
         if sagemaker.estimator.DIR_PARAM_NAME.upper() in environment:
@@ -161,7 +169,7 @@ def serve(self, model_dir, environment):
         _ecr_login_if_needed(self.sagemaker_session.boto_session, self.image)
 
         self._generate_compose_file('serve',
-                                    additional_env_vars=env_vars,
+                                    additional_env_vars=environment,
                                     additional_volumes=volumes)
         compose_command = self._compose()
         self.container = _HostingContainer(compose_command)
@@ -384,7 +392,8 @@ def _generate_compose_file(self, command, additional_volumes=None, additional_en
         if aws_creds is not None:
             environment.extend(aws_creds)
 
-        environment.extend(additional_env_vars)
+        additional_env_var_list = ['{}={}'.format(k, v) for k, v in additional_env_vars.items()]
+        environment.extend(additional_env_var_list)
 
         if command == 'train':
             optml_dirs = {'output', 'output/data', 'input'}
diff --git a/tests/unit/test_image.py b/tests/unit/test_image.py
index 2aed2bff17..be1f8f6ac6 100644
--- a/tests/unit/test_image.py
+++ b/tests/unit/test_image.py
@@ -49,12 +49,14 @@
     }
 ]
 HYPERPARAMETERS = {'a': 1,
-                   'b': 'bee',
-                   'sagemaker_submit_directory': json.dumps('s3://my_bucket/code')}
+                   'b': json.dumps('bee'),
+                   'sagemaker_submit_directory': json.dumps('s3://my_bucket/code'),
+                   'sagemaker_job_name': json.dumps('my-job')}
 
 LOCAL_CODE_HYPERPARAMETERS = {'a': 1,
                               'b': 2,
-                              'sagemaker_submit_directory': json.dumps('file:///tmp/code')}
+                              'sagemaker_submit_directory': json.dumps('file:///tmp/code'),
+                              'sagemaker_job_name': json.dumps('my-job')}
 
 
 @pytest.fixture()
@@ -244,6 +246,8 @@ def test_train(_download_folder, _cleanup, popen, _stream_output, LocalSession,
             for h in sagemaker_container.hosts:
                 assert config['services'][h]['image'] == image
                 assert config['services'][h]['command'] == 'train'
+                assert 'AWS_REGION={}'.format(REGION) in config['services'][h]['environment']
+                assert 'TRAINING_JOB_NAME=my-job' in config['services'][h]['environment']
 
         # assert that expected by sagemaker container output directories exist
         assert os.path.exists(os.path.join(sagemaker_container.container_root, 'output'))