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

Public health officer

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
Surveillance, the indicator and the alert.
Estimate

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

16%40%+6.4
Outbreak, the questionnaire and the one who will not answer.
Estimate

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

18%14%+2.5
Field, the source and shutting the premises.
Estimate

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

16%28%+4.5
Report, the mayor and not softening the figure.
Estimate

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

16%22%+3.5
Vaccination, coverage and the rumour.
Estimate

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

18%18%+3.2
Cut the outbreak, and not softening it.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • epi surveillance
  • outbreaks
  • field questionnaires
  • shut premises
  • vaccine coverage
  • public-health alerts
  • mayors
  • not soften figures

Sources for this job· O*NET 21-1091.00· ESCO/ISCO 2263

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