CreateAutoMLJob - Amazon SageMaker
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Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.


We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.

CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).

Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.

You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.

Request Syntax

{ "AutoMLJobConfig": { "CandidateGenerationConfig": { "AlgorithmsConfig": [ { "AutoMLAlgorithms": [ "string" ] } ], "FeatureSpecificationS3Uri": "string" }, "CompletionCriteria": { "MaxAutoMLJobRuntimeInSeconds": number, "MaxCandidates": number, "MaxRuntimePerTrainingJobInSeconds": number }, "DataSplitConfig": { "ValidationFraction": number }, "Mode": "string", "SecurityConfig": { "EnableInterContainerTrafficEncryption": boolean, "VolumeKmsKeyId": "string", "VpcConfig": { "SecurityGroupIds": [ "string" ], "Subnets": [ "string" ] } } }, "AutoMLJobName": "string", "AutoMLJobObjective": { "MetricName": "string" }, "GenerateCandidateDefinitionsOnly": boolean, "InputDataConfig": [ { "ChannelType": "string", "CompressionType": "string", "ContentType": "string", "DataSource": { "S3DataSource": { "S3DataType": "string", "S3Uri": "string" } }, "SampleWeightAttributeName": "string", "TargetAttributeName": "string" } ], "ModelDeployConfig": { "AutoGenerateEndpointName": boolean, "EndpointName": "string" }, "OutputDataConfig": { "KmsKeyId": "string", "S3OutputPath": "string" }, "ProblemType": "string", "RoleArn": "string", "Tags": [ { "Key": "string", "Value": "string" } ] }

Request Parameters

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.


A collection of settings used to configure an AutoML job.

Type: AutoMLJobConfig object

Required: No


Identifies an Autopilot job. The name must be unique to your account and is case insensitive.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 32.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,31}

Required: Yes


Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.

Type: AutoMLJobObjective object

Required: No


Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.

Type: Boolean

Required: No


An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

Type: Array of AutoMLChannel objects

Array Members: Minimum number of 1 item. Maximum number of 2 items.

Required: Yes


Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

Type: ModelDeployConfig object

Required: No


Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.

Type: AutoMLOutputDataConfig object

Required: Yes


Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

Type: String

Valid Values: BinaryClassification | MulticlassClassification | Regression

Required: No


The ARN of the role that is used to access the data.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Required: Yes


An array of key-value pairs. You can use tags to categorize your Amazon resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AmazonResources. Tag keys must be unique per resource.

Type: Array of Tag objects

Array Members: Minimum number of 0 items. Maximum number of 50 items.

Required: No

Response Syntax

{ "AutoMLJobArn": "string" }

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.


The unique ARN assigned to the AutoML job when it is created.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 256.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:automl-job/.*


For information about the errors that are common to all actions, see Common Errors.


Resource being accessed is in use.

HTTP Status Code: 400


You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.

HTTP Status Code: 400

See Also

For more information about using this API in one of the language-specific Amazon SDKs, see the following: