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

Energy 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
Energy audit, curves and the saving potential.
Estimate

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

18%48%+8.6
Contracts, tariffs and the power market.
Estimate

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

16%36%+5.8
Plant, meters and what the meter misses.
Estimate

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

16%22%+3.5
Efficiency projects and the real payback.
Estimate

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

16%28%+4.5
The board, the CAPEX and the no to the project.
Estimate

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

18%14%+2.5
Save for real, and not selling green smoke.
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

  • energy audit
  • load curves
  • power tariffs
  • energy efficiency
  • CAPEX payback
  • plant metering
  • power market
  • real savings

Sources for this job· O*NET 17-2199.00· ESCO/ISCO 2149

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