diff --git a/compiler_opt/distributed/local/local_worker_manager.py b/compiler_opt/distributed/local/local_worker_manager.py
index dcf60448..f1838c9b 100644
--- a/compiler_opt/distributed/local/local_worker_manager.py
+++ b/compiler_opt/distributed/local/local_worker_manager.py
@@ -60,6 +60,10 @@ class TaskResult:
   value: Any
 
 
+def _get_context():
+  return multiprocessing.get_context('spawn')
+
+
 SerializedClass = bytes
 
 
@@ -74,6 +78,7 @@ def _run_impl(pipe: connection.Connection, worker_class: SerializedClass, *args,
   # jobs, this effectively limits the number of clang instances spawned.
   pool = concurrent.futures.ThreadPoolExecutor(max_workers=1)
   obj = cloudpickle.loads(worker_class)(*args, **kwargs)
+  obj = cloudpickle.loads(worker_class)(*args, **kwargs)
 
   # Pipes are not thread safe
   pipe_lock = threading.Lock()
@@ -122,7 +127,7 @@ class _Stub:
     """Client stub to a worker hosted by a process."""
 
     def __init__(self):
-      parent_pipe, child_pipe = multiprocessing.get_context().Pipe()
+      parent_pipe, child_pipe = _get_context().Pipe()
       self._pipe = parent_pipe
       self._pipe_lock = threading.Lock()
 
@@ -130,7 +135,7 @@ def __init__(self):
       # we set aside 1 thread to coordinate running jobs, and the main thread
       # to handle high priority requests. The expectation is that the user
       # achieves concurrency through multiprocessing, not multithreading.
-      self._process = multiprocessing.get_context().Process(
+      self._process = _get_context().Process(
           target=functools.partial(_run, child_pipe, cloudpickle.dumps(cls), *
                                    args, **kwargs))
       # lock for the msgid -> reply future map. The map will be set to None