diff --git a/cunumeric/eager.py b/cunumeric/eager.py
index 589f22c05..b3a6212b3 100644
--- a/cunumeric/eager.py
+++ b/cunumeric/eager.py
@@ -659,20 +659,6 @@ def bitgenerator_integers(
                 a = np.random.random_integers(low, high, size=self.array.shape)
                 self.array[:] = a
 
-    def bitgenerator_uniform(
-        self, handle, generatorType, seed, flags, low, high
-    ) -> None:
-        if self.deferred is not None:
-            self.deferred.bitgenerator_uniform(
-                handle, generatorType, seed, flags, low, high
-            )
-        else:
-            if self.array.size == 1:
-                self.array.fill(np.random.uniform(low, high))
-            else:
-                a = np.random.uniform(low, high, size=self.array.shape)
-                self.array[:] = a
-
     def bitgenerator_lognormal(
         self, handle, generatorType, seed, flags, mean, sigma
     ) -> None:
@@ -701,6 +687,20 @@ def bitgenerator_normal(
                 a = np.random.normal(mean, sigma, size=self.array.shape)
                 self.array[:] = a
 
+    def bitgenerator_uniform(
+        self, handle, generatorType, seed, flags, low, high
+    ) -> None:
+        if self.deferred is not None:
+            self.deferred.bitgenerator_uniform(
+                handle, generatorType, seed, flags, low, high
+            )
+        else:
+            if self.array.size == 1:
+                self.array.fill(np.random.uniform(low, high))
+            else:
+                a = np.random.uniform(low, high, size=self.array.shape)
+                self.array[:] = a
+
     def bitgenerator_poisson(
         self, handle, generatorType, seed, flags, lam
     ) -> None:
diff --git a/cunumeric/random/bitgenerator.py b/cunumeric/random/bitgenerator.py
index 702271628..0f3cef328 100644
--- a/cunumeric/random/bitgenerator.py
+++ b/cunumeric/random/bitgenerator.py
@@ -110,6 +110,17 @@ def normal(self, mean=0.0, sigma=1.0, shape=None, dtype=np.float64):
         )
         return res
 
+    def uniform(self, low=0.0, high=1.0, shape=None, dtype=np.float64):
+        if shape is None:
+            shape = (1,)
+        if not isinstance(shape, tuple):
+            shape = (shape,)
+        res = ndarray(shape, dtype=np.dtype(dtype))
+        res._thunk.bitgenerator_uniform(
+            self.handle, self.generatorType, self.seed, self.flags, low, high
+        )
+        return res
+
     def poisson(self, lam, shape=None):
         if shape is None:
             shape = (1,)
diff --git a/cunumeric/random/generator.py b/cunumeric/random/generator.py
index 8bddea675..91583ea6a 100644
--- a/cunumeric/random/generator.py
+++ b/cunumeric/random/generator.py
@@ -41,6 +41,9 @@ def normal(self, loc=0.0, scale=1.0, size=None, dtype=np.float64):
             mean=loc, sigma=scale, shape=size, dtype=dtype
         )
 
+    def uniform(self, low=0.0, high=1.0, size=None, dtype=np.float64):
+        return self.bit_generator.uniform(low, high, size, dtype)
+
     def poisson(self, lam=1.0, size=None):
         return self.bit_generator.poisson(lam, size)
 
diff --git a/src/cunumeric/random/bitgenerator_curand.inl b/src/cunumeric/random/bitgenerator_curand.inl
index fc1aabeb5..ec90acfd4 100644
--- a/src/cunumeric/random/bitgenerator_curand.inl
+++ b/src/cunumeric/random/bitgenerator_curand.inl
@@ -932,7 +932,6 @@ struct BitGeneratorImplBody {
                   std::vector<legate::Store>& args)
   {
     generator_map_t& genmap = get_generator_map();
-    // printtid((int)op);
     switch (op) {
       case BitGeneratorOperation::CREATE: {
         genmap.create(generatorID, generatorType, seed, flags);
diff --git a/tests/integration/test_random_bitgenerator.py b/tests/integration/test_random_bitgenerator.py
index e8fb265c2..6f32158f8 100644
--- a/tests/integration/test_random_bitgenerator.py
+++ b/tests/integration/test_random_bitgenerator.py
@@ -153,6 +153,30 @@ def test_normal_float64(t):
     assert_distribution(a, theo_mean, theo_std)
 
 
+@pytest.mark.parametrize("t", BITGENERATOR_ARGS, ids=str)
+def test_uniform_float32(t):
+    bitgen = t(seed=42)
+    gen = num.random.Generator(bitgen)
+    low = 1.414
+    high = 3.14
+    a = gen.uniform(low, high, size=(1024 * 1024,), dtype=np.float32)
+    theo_mean = (low + high) / 2.0
+    theo_std = (high - low) / np.sqrt(12.0)
+    assert_distribution(a, theo_mean, theo_std)
+
+
+@pytest.mark.parametrize("t", BITGENERATOR_ARGS, ids=str)
+def test_uniform_float64(t):
+    bitgen = t(seed=42)
+    gen = num.random.Generator(bitgen)
+    low = 1.414
+    high = 3.14
+    a = gen.uniform(low, high, size=(1024 * 1024,), dtype=np.float64)
+    theo_mean = (low + high) / 2.0
+    theo_std = (high - low) / np.sqrt(12.0)
+    assert_distribution(a, theo_mean, theo_std)
+
+
 @pytest.mark.parametrize("t", BITGENERATOR_ARGS, ids=str)
 def test_poisson(t):
     bitgen = t(seed=42)