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?
Forklift operator
17%
#577 / 623
View rankingForklift operator
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 |
|---|---|---|---|
Notes, locations and picking routes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Drive, lift and stack.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 8% | +1.9 |
Loads, centres of gravity and aisles.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
Shift, radio and dock.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Logs, incidents and counts.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 22% | +3.1 |
Not hitting anyone or a pallet.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
| Total | 100% | 17% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Notes, locations and picking routes
- Drive, lift and stack
- Loads, centres of gravity and aisles
- Shift, radio and dock
- Logs, incidents and counts
- Not hitting anyone or a pallet
- carretillero
- carretilla
- forklift
Sources for this job· O*NET 53-7051.00· ESCO/ISCO 8344