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?
Furniture assembler
19%
#508 / 623
View rankingFurniture assembler
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 |
|---|---|---|---|
Manual, fittings and the parts count.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Assemble, plumb and the wrong screw.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Up the stairs without marking the wall.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Adjust doors, drawers and the client watching.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The small flat and the piece that will not fit whole.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
That it does not wobble, and not leaving a fitting out.EstimateNo 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
Skills and activities
- assemble furniture
- fittings
- plumb wardrobes
- adjust doors
- drawers
- up the stairs
- parts count
- screws
Sources for this job· O*NET 51-2092.00· ESCO/ISCO 8219