diff --git a/ami/main/api/views.py b/ami/main/api/views.py
index 9a2770ac8..ba2a88077 100644
--- a/ami/main/api/views.py
+++ b/ami/main/api/views.py
@@ -13,6 +13,7 @@
 from django_filters.rest_framework import DjangoFilterBackend
 from drf_spectacular.types import OpenApiTypes
 from drf_spectacular.utils import OpenApiParameter, extend_schema
+from pydantic import ValidationError
 from rest_framework import exceptions as api_exceptions
 from rest_framework import filters, serializers, status, viewsets
 from rest_framework.decorators import action
@@ -31,6 +32,8 @@
 from ami.base.views import ProjectMixin
 from ami.main.api.schemas import project_id_doc_param
 from ami.main.api.serializers import TagSerializer
+from ami.ml.models.processing_service import ProcessingService
+from ami.ml.schemas import PipelineRegistrationResponse
 from ami.utils.requests import get_default_classification_threshold
 from ami.utils.storages import ConnectionTestResult
 
@@ -206,6 +209,63 @@ def charts(self, request, pk=None):
         project = self.get_object()
         return Response({"summary_data": project.summary_data()})
 
+    @action(detail=True, methods=["post"], url_path="pipelines")
+    def pipelines(self, request, pk=None):
+        """
+        Receive pipeline registrations for a project. This endpoint is called by the
+        V2 ML processing services to register available pipelines for a project.
+
+        Expected payload: PipelineRegistrationResponse (pydantic schema) containing a
+        list of PipelineConfigResponse objects under the `pipelines` key.
+
+        Behavior:
+        - If the project has no associated ProcessingService, create a dummy one and
+          associate it with the project.
+        - Call ProcessingService.create_pipelines() with the provided pipeline configs
+          and limit the operation to this project.
+
+        Returns the PipelineRegistrationResponse returned by create_pipelines().
+        """
+        # Parse the incoming payload using the pydantic schema so we convert dicts to
+        # the expected PipelineConfigResponse models
+        try:
+            parsed: PipelineRegistrationResponse = PipelineRegistrationResponse.parse_obj(request.data)
+        except ValidationError as err:
+            logger.debug(f"Invalid pipeline registration payload: {err}")
+            return Response({"detail": str(err)}, status=status.HTTP_400_BAD_REQUEST)
+
+        project: Project = self.get_object()
+
+        # TODO: Discuss the right approach for associating pipelines with projects in V2.
+        # For now, we create a dummy processing service if none exists (hack).
+
+        # Find an existing processing service for this project
+        processing_service = ProcessingService.objects.filter(projects=project).first()
+
+        if not processing_service:
+            # Create a dummy processing service and associate it with the project
+            processing_service = ProcessingService.objects.create(
+                name=f"Dummy Processing Service for project {project.pk}",
+                endpoint_url=f"http://dummy.local/projects/{project.pk}/processing-service",
+            )
+            processing_service.projects.add(project)
+            processing_service.save()
+            logger.info(f"Created dummy processing service {processing_service} for project {project.pk}")
+
+        pipeline_configs = parsed.pipelines if parsed and parsed.pipelines else None
+
+        # Call create_pipelines limited to this project
+        response = processing_service.create_pipelines(
+            pipeline_configs=pipeline_configs,
+            projects=Project.objects.filter(pk=project.pk),
+        )
+
+        # Save any changes to the processing service
+        processing_service.save()
+
+        # response is a pydantic model; return its dict representation
+        return Response(response.dict())
+
     @extend_schema(
         parameters=[
             OpenApiParameter(