fix(mlx): serialize accelerator lifecycle and inference

Route MLX load, inference, unload, reset, cache cleanup, and shutdown through a single worker. Add affinity and concurrent-unload regression coverage.\n\nVerified: 17 related backend tests; frontend CI; cargo check.

backend/services/transcribe.py

@@ -2,21 +2,19 @@
 STT (Speech-to-Text) module - delegates to backend abstraction layer.
 """
 
-from typing import Optional
-from ..backends import get_stt_backend, STTBackend
+from ..backends import STTBackend, get_stt_backend, unload_backend
 
 
 def get_whisper_model() -> STTBackend:
     """
     Get STT backend instance (MLX or PyTorch based on platform).
-    
+
     Returns:
         STT backend instance
     """
     return get_stt_backend()
 
 
-def unload_whisper_model():
-    """Unload Whisper model to free memory."""
-    backend = get_stt_backend()
-    backend.unload_model()
+async def unload_whisper_model():
+    """Unload Whisper model to free memory, serialized onto the MLX worker."""
+    await unload_backend(get_stt_backend())