diff --git a/jobs/sweep_schedulers/optuna_scheduler/optuna_scheduler.py b/jobs/sweep_schedulers/optuna_scheduler/optuna_scheduler.py
index 514a41d..0821672 100644
--- a/jobs/sweep_schedulers/optuna_scheduler/optuna_scheduler.py
+++ b/jobs/sweep_schedulers/optuna_scheduler/optuna_scheduler.py
@@ -650,26 +650,40 @@ def _make_trial(self) -> Tuple[Dict[str, Any], optuna.Trial]:
                 config[param]["value"] = trial.suggest_categorical(
                     param, [extras["value"]]
                 )
+            elif extras.get("distribution"):
+                raise SchedulerError(
+                    "Distributions are deprecated. Please provide 'step' or 'log' with 'min' and 'max'."
+                )
             elif type(extras.get("min")) == float:
                 if not extras.get("max"):
                     raise SchedulerError(
                         "Error converting config. 'min' requires 'max'"
                     )
-                log = "log" in param
+                log = extras.get("log", False)
+                step = extras.get("step")
                 config[param]["value"] = trial.suggest_float(
-                    param, extras["min"], extras["max"], log=log
+                    param, extras["min"], extras["max"], log=log, step=step
                 )
             elif type(extras.get("min")) == int:
                 if not extras.get("max"):
                     raise SchedulerError(
                         "Error converting config. 'min' requires 'max'"
                     )
-                log = "log" in param
-                config[param]["value"] = trial.suggest_int(
-                    param, extras["min"], extras["max"], log=log
-                )
+                log = extras.get("log", False)
+                step = extras.get("step")
+                if step:
+                    config[param]["value"] = trial.suggest_int(
+                        param, extras["min"], extras["max"], log=log, step=step
+                    )
+                else:
+                    config[param]["value"] = trial.suggest_int(
+                        param, extras["min"], extras["max"], log=log
+                    )
             else:
                 logger.debug(f"Unknown parameter type: param={param}, val={extras}")
+                raise SchedulerError(
+                    f"Error converting config. Unknown parameter type: param={param}, val={extras}"
+                )
         return config, trial
 
     def _make_trial_from_objective(self) -> Tuple[Dict[str, Any], optuna.Trial]: