# Jobs

## Overview

AI Jobs are background operations used by datasets, projects, runs, and models. The Jobs page gives the team one place to monitor
queued work, inspect failures, and open completed results.

> **Note**
> Jobs are scoped to the active team and user filters. If expected work is missing, confirm the selected team and clear the Group, Status, and Type filters.

## Monitor AI Jobs

Open [Luxonis Hub](https://hub.luxonis.com/ai/jobs) and select Jobs under AI & Models. The table shows each job's name, type,
status, start time, finish time, and result link when available.

Use Group to switch between team and user work, Status to isolate active or failed jobs, and Type to find a specific operation. A
failed row exposes error details that can help identify invalid data or configuration.

Use the result action to open a training run, evaluation run, or model instance. Completed dataset exports show Download Export
instead. Results remain on their owning resource even though the background work is summarized here.

The Hub dashboard also includes an AI Jobs card for a quick view of recent activity.

## Status reference

| Status | Meaning |
| --- | --- |
| Queued | The job is waiting for required resources or earlier pipeline work |
| Running | Background work is active |
| Completed | The operation succeeded and its result is available |
| Failed | The operation ended with an error; inspect the job details or owning resource logs |
| Shutdown | The work was stopped before normal completion |

## Job types by domain

The exact Type list evolves as Hub AI adds workflows. Common jobs include:

| Domain | Examples |
| --- | --- |
| Datasets | Upload Batch Samples ZIP, Ingest Samples from Snaps, Batch Samples Update, Create Dataset Version, Dataset Export,
Preannotation |
| Annotation services | Start Inference Engine, Generate Sample Thumbnail |
| Projects and runs | Version and Start Training Run, Training Run |
| Models | Upload and Convert Model, Model Conversion, Upload Model Instance Files, Update NN Archive Config |

For dataset-specific results, see [Create, Upload & Export](https://docs.luxonis.com/cloud/hubai/training/datasets/upload.md). For
run preparation and controls, see [Training & Evaluation Runs](https://docs.luxonis.com/cloud/hubai/training/runs.md).