diff --git a/torch/profiler/profiler.py b/torch/profiler/profiler.py
index 939ae73a99af..4b0708c4a78f 100644
--- a/torch/profiler/profiler.py
+++ b/torch/profiler/profiler.py
@@ -36,6 +36,28 @@ __all__ = [
 PROFILER_STEP_NAME = "ProfilerStep"
 
 
+class _NumpyEncoder(json.JSONEncoder):
+    """
+    Json encoder for numpy types (np.int, np.float, np.array etc.)
+    Returns default encoder if numpy is not available
+    """
+
+    def default(self, obj):
+        """Encode NumPy types to JSON"""
+        try:
+            import numpy as np
+        except ImportError:
+            return json.JSONEncoder.default(self, obj)
+        if isinstance(obj, np.integer):
+            return int(obj)
+        elif isinstance(obj, np.floating):
+            return float(obj)
+        elif isinstance(obj, np.ndarray):
+            return obj.tolist()
+        else:
+            return json.JSONEncoder.default(self, obj)
+
+
 def supported_activities():
     """
     Returns a set of supported profiler tracing activities.
@@ -187,7 +209,9 @@ class _KinetoProfile:
         if kineto_available():
             dist_info = self._get_distributed_info()
             if dist_info:
-                self.add_metadata_json("distributedInfo", json.dumps(dist_info))
+                self.add_metadata_json(
+                    "distributedInfo", json.dumps(dist_info, cls=_NumpyEncoder)
+                )
 
             if hasattr(torch, "_inductor"):
                 import torch._inductor.config as inductor_config
@@ -931,5 +955,6 @@ class ExecutionTraceObserver(_ITraceObserver):
         ):
             pg_config_info = torch.distributed.distributed_c10d._world.pg_config_info
             torch.autograd._record_function_with_args_enter(
-                "## process_group:init ##", json.dumps(pg_config_info)
+                "## process_group:init ##",
+                json.dumps(pg_config_info, cls=_NumpyEncoder),
             )