diff --git a/job/__init__.py b/job/__init__.py
new file mode 100644
index 0000000..a8d0874
--- /dev/null
+++ b/job/__init__.py
@@ -0,0 +1 @@
+from .sobo import sobo_job
\ No newline at end of file
diff --git a/job/sobo.py b/job/sobo.py
new file mode 100644
index 0000000..6ea2c64
--- /dev/null
+++ b/job/sobo.py
@@ -0,0 +1,41 @@
+import os
+import bo
+import ptycho
+
+def sobo_job(config):
+
+    print("Hello")
+    # result_dir = config['io']['result_dir']
+    # os.makedirs(result_dir, exist_ok=True)
+
+    # randombo = bo.RandomBOEngine(config)
+
+    # bo_txt = os.path.join(result_dir, "bo.txt")
+    # with open(bo_txt, "w") as f:
+    #     f.write(f"    iter\tmetric\t{"\t".join([p[:7] for p in randombo.params])}\n")
+
+    # for j in range(J):
+    #     print(f"RANDOM sampling iteration {j}")
+    #     job_config = randombo.ask()
+    #     ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config)
+    #     ptycho_engine.run(run_id=f"bo-{j:03d}")
+    #     y_value = ptycho_engine._metric
+    #     randombo.tell(job_config, y_value)
+    #     with open(bo_txt, "a") as f:
+    #         p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in randombo.params]
+    #         f.write(f"{j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")
+
+
+    # sobo = bo.SingleObjectiveBOEngine(config)
+    # sobo.train_x = randombo.train_x
+    # sobo.train_y = randombo.train_y
+    # for j in range(J, J + config['bo']['max_iterations'] + 1):
+    #     print(f"SOBO sampling iteration {j}")
+    #     job_config = sobo.ask()
+    #     ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config)
+    #     ptycho_engine.run(run_id=f"bo-{j:03d}")
+    #     y_value = ptycho_engine._metric
+    #     sobo.tell(job_config, y_value)
+    #     with open(bo_txt, "a") as f:
+    #         p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in sobo.params]
+    #         f.write(f"{j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")
\ No newline at end of file
diff --git a/main.py b/main.py
index d4b5b9d..84a1a38 100644
--- a/main.py
+++ b/main.py
@@ -1,54 +1,19 @@
-import os
 import sys
 import yaml
-import shutil
-import numpy as np
 
-import bo
-import ptycho
+import job
 
 def main(config_yaml):
 
     with open(config_yaml, 'r') as f:
         config = yaml.safe_load(f)
 
-    result_dir = config['io']['result_dir']
-    os.makedirs(result_dir, exist_ok=True)
-    shutil.copy(config_yaml, os.path.join(result_dir, os.path.basename(config_yaml)))
+    job_types = {
+        'random+sobo': job.sobo_job
+    }
 
-    # RANDOM BO SAMPLING PREPARATIONS; 20 SAMPLES
-    J = 20
-    randombo = bo.RandomBOEngine(config)
-
-    bo_txt = os.path.join(result_dir, "bo.txt")
-    with open(bo_txt, "w") as f:
-        f.write(f"    iter\tmetric\t{"\t".join([p[:7] for p in randombo.params])}\n")
-
-    for j in range(J):
-        print(f"RANDOM sampling iteration {j}")
-        job_config = randombo.ask()
-        ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config)
-        ptycho_engine.run(run_id=f"bo-{j:03d}")
-        y_value = ptycho_engine._metric
-        randombo.tell(job_config, y_value)
-        with open(bo_txt, "a") as f:
-            p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in randombo.params]
-            f.write(f"{j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")
-
-    # MAIN SINGLE OBJECTIVE BAYESIAN OPTIMIZATION
-    sobo = bo.SingleObjectiveBOEngine(config)
-    sobo.train_x = randombo.train_x
-    sobo.train_y = randombo.train_y
-    for j in range(J, J + config['bo']['max_iterations'] + 1):
-        print(f"SOBO sampling iteration {j}")
-        job_config = sobo.ask()
-        ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config)
-        ptycho_engine.run(run_id=f"bo-{j:03d}")
-        y_value = ptycho_engine._metric
-        sobo.tell(job_config, y_value)
-        with open(bo_txt, "a") as f:
-            p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in sobo.params]
-            f.write(f"{j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")
+    job_types[config['job']['type']](config)
+    
 
 if __name__ == "__main__":
     if len(sys.argv) != 2: