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 / 623
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?
Domestic worker
15%
#613 / 623
View rankingDomestic worker
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 |
|---|---|---|---|
Lists, online shopping and written errands.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 30% | +4.2 |
Menus and pantry organisation.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 22% | +2.6 |
Clean, cook, iron and tidy.EstimateNo public source provides a precise figure. This is our estimate. | 26% | 8% | +2.1 |
Care for elders or children of the house.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 10% | +1.6 |
Trust, keys and boundaries.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
Relationship with the employing family.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 15% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Lists, online shopping and written errands
- Menus and pantry organisation
- Clean, cook, iron and tidy
- Care for elders or children of the house
- Trust, keys and boundaries
- Relationship with the employing family
- empleada de hogar
- interno
- domestic worker
- trabajadora del hogar
Sources for this job· O*NET 39-9011.00· ESCO/ISCO 9111