diff --git a/skyrl/backends/skyrl_train/workers/worker.py b/skyrl/backends/skyrl_train/workers/worker.py
index 43a73fc28c..d0ae5af0cc 100644
--- a/skyrl/backends/skyrl_train/workers/worker.py
+++ b/skyrl/backends/skyrl_train/workers/worker.py
@@ -1,7 +1,9 @@
 import asyncio
 import logging
 import os
+import signal
 import socket
+import sys
 from collections import defaultdict
 from ctypes import CDLL, POINTER, Structure, c_char_p, c_int, c_ulong, c_void_p
 from datetime import timedelta
@@ -121,6 +123,29 @@ def init_worker_process_group(self):
                 backend="cpu:gloo,cuda:nccl", timeout=timedelta(seconds=SKYRL_WORKER_NCCL_TIMEOUT_IN_S)
             )
 
+        # Clean teardown on k8s SIGTERM: drain CUDA streams + release NCCL
+        # communicators before the 25s grace period elapses.
+        rank = self._rank
+
+        def _sigterm_cleanup(signum, frame):
+            logger.warning(f"SIGTERM received in worker rank={rank}, cleaning up...")
+
+            if torch.cuda.is_available():
+                try:
+                    torch.cuda.synchronize()
+                except Exception as e:
+                    logger.warning(f"cuda.synchronize() failed: {e}")
+
+            try:
+                if torch.distributed.is_available() and torch.distributed.is_initialized():
+                    torch.distributed.destroy_process_group()
+            except Exception as e:
+                logger.warning(f"destroy_process_group() failed: {e}")
+
+            sys.exit(0)
+
+        signal.signal(signal.SIGTERM, _sigterm_cleanup)
+
         # setup device mesh
         # TODO: Support TP / PP for additional backends
         # NOTE (sumanthrh): Device mesh and mesh rank are rank specific attributes. For the current way the strategy is defined,