The Index · ML engineering
ML engineering
Training, serving and monitoring models — MLOps, feature stores, drift, ONNX/TensorRT. `model-evaluation` only covers scoring output; a computer-vision or MLOps capability had no home. tashan measures 8 capabilities for this work and ranks them by tashan score — a transparent composite of upkeep, freshness and real adoption. How we measure ›
| # | Capability | tashan | Evidence | Health |
|---|---|---|---|---|
| 1 | Other | 71 | 3k/wk | active |
| 2 | Docs & Knowledge | 67 | 637/wk | active |
| 3 | Productivity | 63 | 275/wk | active |
| 4 | Finance & Crypto | 55 | 84/wk | active |
| 5 | Search | 49 | 240 ★ | active |
| 6 | Data & Analytics | 37 | 38/wk | active |
| 7 | Cloud & Infra | 33 | 66/wk | active |
| 8 | AI & Agents | 30 | 64/wk | abandoned |
Who does this work
O*NET records this as a core process step for 8 occupations, including Astronomers, Biostatisticians, Mathematicians, Operations Research Analysts, Physicists, Quality Control Analysts, Software Developers, Statisticians.
Recorded there as: "Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields". We publish it under the name practitioners use.
Other work
Occupational data from the O*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration, used under CC BY 4.0. tashan consolidated its process steps into the terms practitioners use; O*NET does not endorse this site.