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 / 643
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?
Addiction doctor
22%
#359 / 643
View rankingAddiction doctor
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 |
|---|---|---|---|
History, AUDIT and the urine screen.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Clinic, the relapse and the one who does not come.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Methadone, the dose and not rushing the taper.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Detox, the bed and the syndrome.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Family, the stigma and not moralising.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Walk the abstinence, and not turning away the one who slips.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
- AUDIT
- methadone
- detox
- relapses
- urine screens
- addiction clinic
- withdrawal
- not moralise
Sources for this job· O*NET 29-1223.00· ESCO/ISCO 2212