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?
Crime scene technician
23%
#315 / 623
View rankingCrime scene 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 |
|---|---|---|---|
Inspection, photos and the scene sketch.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Collect traces, prints and the DNA that gets walked on.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Chain of custody, labels and the lab.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Report, reconstruction and the file.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The dirty scene, the rush and the one who enters ungloved.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That it holds in court, and not breaking the chain.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 23% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- collect traces
- fingerprints
- chain of custody
- photograph scenes
- forensic DNA
- scene sketch
- police lab
- not contaminate
Sources for this job· O*NET 19-4092.00· ESCO/ISCO 3119