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

IS WORK OVER?

29%

AI can already do 29% of this job.

#64 / 623

ML engineer

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.

Task	Share	AI	Points
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
Total	100%		29%

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

IS WORK OVER?

19%

#496 / 623

Shutter installer

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.

Task	Share	AI	Points
Measure, order and the box that will not fit. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Box, axle and the motor in the opening. Estimate No public source provides a precise figure. This is our estimate.	22%	8%	+1.8
Tape, slats and the one that derails. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Program the remote and the limit. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The neighbour, the inner courtyard and not scratching the frame. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
That it runs true, and not leaving a lame box. Estimate No public source provides a precise figure. This is our estimate.	14%	12%	+1.7
Total	100%		19%

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