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

Taxidermist

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
Skin, tan and the form.
Estimate

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

16%32%+5.1
Mount, set the eyes and the expression.
Estimate

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

18%12%+2.2
Drying, pests and the hair that slips.
Estimate

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

16%28%+4.5
Client, the trophy and what you cannot do.
Estimate

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

16%22%+3.5
CITES, the permit and not mounting the illegal.
Estimate

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

18%18%+3.2
No smell, and the hair in place.
Estimate

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

16%14%+2.2
Total100%21%

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

Skills and activities

  • tan skins
  • mount trophies
  • forms
  • CITES
  • hair
  • expression
  • mount pests
  • permits

Sources for this job· O*NET 27-1012.00· ESCO/ISCO 3431

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