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?

29%

AI can already do 29% of this job.

#64 / 763

ML engineer

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. Estimate No public source provides a precise figure. This is our estimate.	22%	48%	+10.6
Evaluate, document and compare runs. Estimate No public source provides a precise figure. This is our estimate.	18%	42%	+7.6
Deploy, monitor and retrain. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Talk to product about what a good error is. Estimate No public source provides a precise figure. This is our estimate.	16%	15%	+2.4
Dirty data, bias and model limits. Estimate No public source provides a precise figure. This is our estimate.	14%	18%	+2.5
On-call, incidents and rollback. Estimate No 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

IS WORK OVER?

27%

#151 / 763

Backend developer

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
Endpoint, the contract and the test. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Spike, the queue and the one that drops. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Key, the secret and not leaving it in the repo. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Migration, the rollback and not improvising in prod. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Product, the deadline and not cutting the one that matters. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
That it takes the spike, and not leaving the key. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		27%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low