diff --git a/web/apps/photos/src/services/face/blur.ts b/web/apps/photos/src/services/face/blur.ts
index 71420b1df..c79081297 100644
--- a/web/apps/photos/src/services/face/blur.ts
+++ b/web/apps/photos/src/services/face/blur.ts
@@ -1,6 +1,6 @@
 import { Face } from "services/face/types";
 import { createGrayscaleIntMatrixFromNormalized2List } from "utils/image";
-import { mobileFaceNetFaceSize } from "../machineLearning/embed";
+import { mobileFaceNetFaceSize } from "./embed";
 
 /**
  * Laplacian blur detection.
diff --git a/web/apps/photos/src/services/machineLearning/embed.ts b/web/apps/photos/src/services/face/embed.ts
similarity index 94%
rename from web/apps/photos/src/services/machineLearning/embed.ts
rename to web/apps/photos/src/services/face/embed.ts
index 5dfbf7061..2e0977ea1 100644
--- a/web/apps/photos/src/services/machineLearning/embed.ts
+++ b/web/apps/photos/src/services/face/embed.ts
@@ -8,7 +8,7 @@ export const mobileFaceNetFaceSize = 112;
  *
  * The model used is MobileFaceNet, running in an ONNX runtime.
  */
-export const getFaceEmbeddings = async (
+export const faceEmbeddings = async (
     faceData: Float32Array,
 ): Promise<Array<FaceEmbedding>> => {
     const outputData = await workerBridge.faceEmbeddings(faceData);
diff --git a/web/apps/photos/src/services/face/types.ts b/web/apps/photos/src/services/face/types.ts
index d09380791..44b3321f6 100644
--- a/web/apps/photos/src/services/face/types.ts
+++ b/web/apps/photos/src/services/face/types.ts
@@ -199,7 +199,6 @@ export interface MLSyncContext {
     userID: number;
 
     faceCropService: FaceCropService;
-    faceEmbeddingService: FaceEmbeddingService;
 
     localFilesMap: Map<number, EnteFile>;
     outOfSyncFiles: EnteFile[];
@@ -248,13 +247,6 @@ export interface FaceCropService {
     ): Promise<FaceCrop>;
 }
 
-export interface FaceEmbeddingService {
-    method: Versioned<FaceEmbeddingMethod>;
-    faceSize: number;
-
-    getFaceEmbeddings(faceImages: Float32Array): Promise<Array<FaceEmbedding>>;
-}
-
 export interface MachineLearningWorker {
     closeLocalSyncContext(): Promise<void>;
 
diff --git a/web/apps/photos/src/services/machineLearning/faceService.ts b/web/apps/photos/src/services/machineLearning/faceService.ts
index c358cc291..80bda398a 100644
--- a/web/apps/photos/src/services/machineLearning/faceService.ts
+++ b/web/apps/photos/src/services/machineLearning/faceService.ts
@@ -3,6 +3,7 @@ import log from "@/next/log";
 import { faceAlignment } from "services/face/align";
 import mlIDbStorage from "services/face/db";
 import { detectFaces, getRelativeDetection } from "services/face/detect";
+import { faceEmbeddings, mobileFaceNetFaceSize } from "services/face/embed";
 import {
     DetectedFace,
     Face,
@@ -11,9 +12,9 @@ import {
     type FaceAlignment,
 } from "services/face/types";
 import { imageBitmapToBlob, warpAffineFloat32List } from "utils/image";
+import { detectBlur } from "../face/blur";
 import { clusterFaces } from "../face/cluster";
 import { getFaceCrop } from "../face/crop";
-import { detectBlur } from "../face/blur";
 import {
     fetchImageBitmap,
     fetchImageBitmapForContext,
@@ -86,7 +87,7 @@ class FaceService {
         const faceAlignments = newMlFile.faces.map((f) => f.alignment);
         const faceImages = await extractFaceImagesToFloat32(
             faceAlignments,
-            syncContext.faceEmbeddingService.faceSize,
+            mobileFaceNetFaceSize,
             imageBitmap,
         );
         const blurValues = detectBlur(faceImages, newMlFile.faces);
@@ -104,15 +105,15 @@ class FaceService {
         alignedFacesInput: Float32Array,
     ) {
         const { newMlFile } = fileContext;
-        newMlFile.faceEmbeddingMethod = syncContext.faceEmbeddingService.method;
+        newMlFile.faceEmbeddingMethod = {
+            value: "MobileFaceNet",
+            version: 2,
+        };
         // TODO: when not storing face crops, image will be needed to extract faces
         // fileContext.imageBitmap ||
         //     (await this.getImageBitmap(fileContext));
 
-        const embeddings =
-            await syncContext.faceEmbeddingService.getFaceEmbeddings(
-                alignedFacesInput,
-            );
+        const embeddings = await faceEmbeddings(alignedFacesInput);
         newMlFile.faces.forEach((f, i) => (f.embedding = embeddings[i]));
 
         log.info("[MLService] facesWithEmbeddings: ", newMlFile.faces.length);
diff --git a/web/apps/photos/src/services/machineLearning/machineLearningService.ts b/web/apps/photos/src/services/machineLearning/machineLearningService.ts
index ea75074a3..8e5c7b103 100644
--- a/web/apps/photos/src/services/machineLearning/machineLearningService.ts
+++ b/web/apps/photos/src/services/machineLearning/machineLearningService.ts
@@ -15,8 +15,6 @@ import {
     Face,
     FaceCropService,
     FaceDetection,
-    FaceEmbeddingMethod,
-    FaceEmbeddingService,
     Landmark,
     MLLibraryData,
     MLSearchConfig,
@@ -31,7 +29,6 @@ import { EnteFile } from "types/file";
 import { isInternalUserForML } from "utils/user";
 import { fetchImageBitmapForContext } from "../face/image";
 import { syncPeopleIndex } from "../face/people";
-import mobileFaceNetEmbeddingService from "./embed";
 import FaceService from "./faceService";
 
 /**
@@ -105,24 +102,11 @@ export async function updateMLSearchConfig(newConfig: MLSearchConfig) {
     return mlIDbStorage.putConfig(ML_SEARCH_CONFIG_NAME, newConfig);
 }
 
-export class MLFactory {
-    public static getFaceEmbeddingService(
-        method: FaceEmbeddingMethod,
-    ): FaceEmbeddingService {
-        if (method === "MobileFaceNet") {
-            return mobileFaceNetEmbeddingService;
-        }
-
-        throw Error("Unknon face embedding method: " + method);
-    }
-}
-
 export class LocalMLSyncContext implements MLSyncContext {
     public token: string;
     public userID: number;
 
     public faceCropService: FaceCropService;
-    public faceEmbeddingService: FaceEmbeddingService;
 
     public localFilesMap: Map<number, EnteFile>;
     public outOfSyncFiles: EnteFile[];
@@ -148,9 +132,6 @@ export class LocalMLSyncContext implements MLSyncContext {
         this.token = token;
         this.userID = userID;
 
-        this.faceEmbeddingService =
-            MLFactory.getFaceEmbeddingService("MobileFaceNet");
-
         this.outOfSyncFiles = [];
         this.nSyncedFiles = 0;
         this.nSyncedFaces = 0;