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?
Private-hire driver
20%
#440 / 623
View rankingPrivate-hire driver
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 |
|---|---|---|---|
App, routes and airport times.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Drive, pick up and drop the client.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 10% | +2.2 |
Car, cleanliness and maintenance.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Service, bags and difficult clients.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Shifts, fatigue and zones.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not missing a flight or a passenger.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
| Total | 100% | 20% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- drive
- route
- load goods
- App, routes and airport times
- Drive, pick up and drop the client
- Car, cleanliness and maintenance
- Service, bags and difficult clients
- Shifts, fatigue and zones
- Not missing a flight or a passenger
- conductor vtc
Sources for this job· O*NET 53-3051.00· ESCO/ISCO 8322