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 / 653
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?
Sterile processing technician
19%
#557 / 653
View rankingSterile processing technician
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 |
|---|---|---|---|
Intake, the dirty and the count.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Wash, the ultrasonic and what is left.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Pack, the indicator and the set.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Autoclave, the load and the cycle that fails.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Theatre, the rush and not sending a wet set.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Truly sterile, and not mixing the dirty.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
- autoclave
- surgical sets
- biological indicators
- ultrasonic wash
- sterile pack
- instrument count
- steam cycles
- not mix dirty
Sources for this job· O*NET 31-9093.00· ESCO/ISCO 3213