IS WORK OVER?

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

ML 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.

TaskShareAIPoints
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
Total100%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

Video editor

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.

TaskShareAIPoints
Select and combine the most effective shots of each scene to form a logical and smoothly running story.
Estimate

No public source provides a precise figure. This is our estimate.

7%28%+2
Edit films and videotapes to insert music, dialogue, and sound effects, to arrange films into sequences, and to correct errors, using editing equipment.
Estimate

No public source provides a precise figure. This is our estimate.

7%28%+2
Set up and operate computer editing systems, electronic titling systems, video switching equipment, and digital video effects units to produce a final product.
Estimate

No public source provides a precise figure. This is our estimate.

7%28%+2
Organize and string together raw footage into a continuous whole according to scripts or the instructions of directors and producers.
Estimate

No public source provides a precise figure. This is our estimate.

7%28%+2
Review footage sequence by sequence to become familiar with it before assembling it into a final product.
Estimate

No public source provides a precise figure. This is our estimate.

6%28%+1.7
Mark frames where a particular shot or piece of sound is to begin or end.
Estimate

No public source provides a precise figure. This is our estimate.

6%28%+1.7
Verify key numbers and time codes on materials.
Estimate

No public source provides a precise figure. This is our estimate.

6%28%+1.7
Cut shot sequences to different angles at specific points in scenes, making each individual cut as fluid and seamless as possible.
Estimate

No public source provides a precise figure. This is our estimate.

6%28%+1.7
Other less frequent tasks (weight estimated from frequency).
Estimate

No public source provides a precise figure. This is our estimate.

48%28%+13.4
Total100%28%

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

Skills and activities

  • personal directing styles
  • film production process
  • graphic design
  • motion graphics
  • ICT software specifications
  • multimedia systems
  • follow work schedule
  • consult with producer
  • watch scenes
  • put uncut recordings into computer

Sources for this job· O*NET 27-4032.00· ESCO/ISCO 2654

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