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?
University professor
24%
#278 / 623
View rankingUniversity professor
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 |
|---|---|---|---|
Prep materials, tests and rubrics.EstimateNo public source provides a precise figure. This is our estimate. | 20% | 45% | +9 |
Papers, grants and reviews.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 38% | +6.1 |
Teach and tutor.EstimateNo public source provides a precise figure. This is our estimate. | 20% | 12% | +2.4 |
Supervise theses and examine.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 15% | +2.4 |
Department meetings and academic admin.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
Actually research and choose the problem.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 16% | +2.2 |
| Total | 100% | 24% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- teach class
- mark students
- lesson plans
- teach
- Prep materials, tests and rubrics
- Papers, grants and reviews
- Teach and tutor
- Supervise theses and examine
- Department meetings and academic admin
- Actually research and choose the problem
Sources for this job· O*NET 25-1081.00· ESCO/ISCO 2310