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 / 703
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?
Employment lawyer
27%
#129 / 703
View rankingEmployment lawyer
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 |
|---|---|---|---|
Letter, the file and the deadline.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Conciliation, the SMAC and not yielding extra.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Hearing, the witness and the one who does not show.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The agreement, the article and not making it up.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The client, the rush and not signing what cannot be.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Stand it up, and not selling an easy yes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- dismissals
- SMAC
- labour conciliation
- employment hearings
- collective agreements
- disciplinary files
- dismissal letters
- labour deadlines
Sources for this job· O*NET 23-1011.00· ESCO/ISCO 2611