diff --git a/model_manager/workflows/train_model.py b/model_manager/workflows/train_model.py
index 3f41f5e..69aa7c5 100644
--- a/model_manager/workflows/train_model.py
+++ b/model_manager/workflows/train_model.py
@@ -16,7 +16,7 @@ with workflow.unsafe.imports_passed_through():
     from datetime import timedelta
     from typing import Any
 
-    from sientia_do.temporal.policies import retry_policy
+    from temporalio.common import RetryPolicy
 
     from model_manager.activities.activities import Activities
     from model_manager.activities.experiment_tracking import UpdateType
@@ -34,6 +34,44 @@ with workflow.unsafe.imports_passed_through():
     TIMEOUT_DELETE_FILE = int(os.getenv('TIMEOUT_DELETE_FILE', '60'))
     TIMEOUT_UPDATE_DATABASE = int(os.getenv('TIMEOUT_UPDATE_DATABASE', '30'))
 
+    # Retry Policies - Granular strategies for different operation types
+    # Fast retry for transient network errors (MinIO operations)
+    network_retry_policy = RetryPolicy(
+        initial_interval=timedelta(seconds=1),
+        maximum_interval=timedelta(seconds=10),
+        backoff_coefficient=2.0,
+        maximum_attempts=5,
+    )
+
+    # No retry for training - data errors are permanent
+    no_retry_policy = RetryPolicy(
+        maximum_attempts=1,
+    )
+
+    # Moderate retry with backoff for MLFlow operations
+    mlflow_retry_policy = RetryPolicy(
+        initial_interval=timedelta(seconds=5),
+        maximum_interval=timedelta(seconds=30),
+        backoff_coefficient=2.0,
+        maximum_attempts=3,
+    )
+
+    # Database retry with exponential backoff
+    database_retry_policy = RetryPolicy(
+        initial_interval=timedelta(seconds=2),
+        maximum_interval=timedelta(seconds=20),
+        backoff_coefficient=2.0,
+        maximum_attempts=5,
+    )
+
+    # Filesystem retry for cleanup operations
+    filesystem_retry_policy = RetryPolicy(
+        initial_interval=timedelta(seconds=2),
+        maximum_interval=timedelta(seconds=10),
+        backoff_coefficient=1.5,
+        maximum_attempts=3,
+    )
+
 
 @workflow.defn(name='train_model')
 class TrainModel:
@@ -183,7 +221,7 @@ class TrainModel:
             train_params = await workflow.execute_activity_method(
                 Activities.validate_train_params,
                 validation_input,
-                retry_policy=retry_policy,
+                retry_policy=no_retry_policy,  # Validation errors are permanent
                 start_to_close_timeout=timedelta(seconds=TIMEOUT_VALIDATE_PARAMS),
             )
 
@@ -253,7 +291,7 @@ class TrainModel:
             uploaded_file = await workflow.execute_activity_method(
                 Activities.fetch_file_from_minio,
                 download_input,
-                retry_policy=retry_policy,
+                retry_policy=network_retry_policy,  # Fast retry for network issues
                 start_to_close_timeout=timedelta(seconds=TIMEOUT_DOWNLOAD_FILE),
             )
 
@@ -267,7 +305,7 @@ class TrainModel:
             train_result = await workflow.execute_activity_method(
                 Activities.train_model,
                 train_input,
-                retry_policy=retry_policy,
+                retry_policy=no_retry_policy,  # Training errors are permanent (bad data)
                 start_to_close_timeout=timedelta(seconds=TIMEOUT_TRAIN_MODEL),
             )
 
@@ -340,7 +378,7 @@ class TrainModel:
             saved_result = await workflow.execute_activity_method(
                 Activities.save_model,
                 save_input,
-                retry_policy=retry_policy,
+                retry_policy=mlflow_retry_policy,  # Retry MLFlow with backoff
                 start_to_close_timeout=timedelta(seconds=TIMEOUT_SAVE_MODEL),
             )
 
@@ -406,7 +444,7 @@ class TrainModel:
                 await workflow.execute_activity_method(
                     Activities.cleanup_run_directory,
                     cleanup_input,
-                    retry_policy=retry_policy,
+                    retry_policy=filesystem_retry_policy,  # Retry filesystem operations
                     start_to_close_timeout=timedelta(seconds=TIMEOUT_CLEANUP_DIRECTORY),
                 )
 
@@ -424,7 +462,7 @@ class TrainModel:
             await workflow.execute_activity_method(
                 Activities.delete_file_from_minio,
                 delete_input,
-                retry_policy=retry_policy,
+                retry_policy=network_retry_policy,  # Fast retry for network issues
                 start_to_close_timeout=timedelta(seconds=TIMEOUT_DELETE_FILE),
             )
 
@@ -496,6 +534,6 @@ class TrainModel:
         await workflow.execute_activity_method(
             Activities.update_experiment_run,
             update_input,
-            retry_policy=retry_policy,
+            retry_policy=database_retry_policy,  # Retry DB with exponential backoff
             start_to_close_timeout=timedelta(seconds=TIMEOUT_UPDATE_DATABASE),
         )