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?
BI analyst
34%
#18 / 623
View rankingBI analyst
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 |
|---|---|---|---|
Model data, light ETL and dashboards.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Write SQL, measures and docs.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 50% | +9 |
Define KPIs with the business and negotiate meaning.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Present insights and defend the number.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Data quality, alerts and lineage.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 15% | +2.1 |
Prioritise requests and say no.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 20% | +2.4 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Model data, light ETL and dashboards
- Write SQL, measures and docs
- Present insights and defend the number
- Data quality, alerts and lineage
- Prioritise requests and say no
- business intelligence
- analista bi
- power bi
- looker
Sources for this job· O*NET 15-2051.00· ESCO/ISCO 2511