IS WORK OVER?

Automation index

How much of a ML engineer’s job can AI already do?

Training a baseline and a notebook is fast. Shipping it, watching drift, and owning the miss is not.

This percentage does not predict how many people will lose their jobs.

Task comparison

ML engineer

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Train models, features and notebooks.
Estimate

No public source provides a precise figure. This is our estimate.

22%48%+10.6
Evaluate, document and compare runs.
Estimate

No public source provides a precise figure. This is our estimate.

18%42%+7.6
Deploy, monitor and retrain.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Talk to product about what a good error is.
Estimate

No public source provides a precise figure. This is our estimate.

16%15%+2.4
Dirty data, bias and model limits.
Estimate

No public source provides a precise figure. This is our estimate.

14%18%+2.5
On-call, incidents and rollback.
Estimate

No public source provides a precise figure. This is our estimate.

14%16%+2.2
Total100%29%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • Train models, features and notebooks
  • Evaluate, document and compare runs
  • Deploy, monitor and retrain
  • Talk to product about what a good error is
  • Dirty data, bias and model limits
  • On-call, incidents and rollback
  • machine learning engineer
  • ingeniero ml
  • mlops

Sources for this job· O*NET 15-1221.00· ESCO/ISCO 2511

Storyboard artist

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Script, shots and the rhythm.
Estimate

No public source provides a precise figure. This is our estimate.

18%48%+8.6
Draw, arrows and the one that does not read.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Review, the director and the scene change.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Delivery, numbering and the missing one.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The budget, the impossible and not drawing a shoot that will not fit.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it can be shot, and that it reads.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%27%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • shots
  • camera arrows
  • rhythm
  • shooting script
  • numbering
  • review with direction
  • scenes
  • board delivery

Sources for this job· O*NET 27-1014.00· ESCO/ISCO 2166

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