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?
ML engineer
29%
AI can already do 29% of this job.
#64 / 673
View rankingML 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.
| Task | Share | AI | Points |
|---|---|---|---|
Train models, features and notebooks.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 48% | +10.6 |
Evaluate, document and compare runs.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 42% | +7.6 |
Deploy, monitor and retrain.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to product about what a good error is.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 15% | +2.4 |
Dirty data, bias and model limits.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 18% | +2.5 |
On-call, incidents and rollback.EstimateNo 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
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
IS WORK OVER?
Art teacher
22%
#394 / 673
View rankingArt teacher
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.
| Task | Share | AI | Points |
|---|---|---|---|
Project, the sheet and the kit.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Classroom, the one who will not dare and the one who bins it.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Technique, the mistake and not doing it for them.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Show, the corridor and not hanging only the pretty.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Staff, 'it's a soft subject', and not dropping the bar.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they get dirty, and not copying the model.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- art sheets
- art projects
- technique
- school shows
- classroom kit
- not do it for them
- the bar
- getting dirty
Sources for this job· O*NET 25-2031.00· ESCO/ISCO 2330