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Occupation · 2026 assessment

Spetsialist po mashinnomu obucheniyu (ml-inzhener)

Spetsialist po mashinnomu obucheniyu (ml-inzhener) is an occupation responsible for building, testing or supporting digital systems and data in a defined technology domain. The profile assesses automation of individual tasks rather than disappearance of the whole occupation.

High risk level Search jobs ↗
How risk may change

A forecast estimate, not a guaranteed scenario.

63%2026
67%2028
72%2030
80%2035

Which tasks are exposed

Risk applies to individual tasks—not to a person or an entire occupation.

TaskRisk
Generating routine code and configuration89%
Preparing tests and technical documentation85%
Classifying errors and analyzing logs77%
Data migrations and routine integrations80%
Architecture and technical trade-offs52%
Security and production accountability32%

Task map

AI replaces ↔ AI augments

Each task is positioned by AI capability and the degree of human involvement still required.

  1. 1Generating routine code and configurationAI 89% · human 41%
  2. 2Preparing tests and technical documentationAI 85% · human 50%
  3. 3Classifying errors and analyzing logsAI 77% · human 42%
  4. 4Data migrations and routine integrationsAI 80% · human 42%
  5. 5Architecture and technical trade-offsAI 52% · human 49%
  6. 6Security and production accountabilityAI 32% · human 65%

Why technology can change this work

  • tools automate data preparation, experiments and parts of modelling
  • code, configuration and documentation are already digital
  • a large share of textual, analytical or information tasks is accessible to current AI models
  • the main inputs and outputs already exist in a digital environment
  • the scale and cost of routine operations create a strong automation incentive
  • routine code, tests and technical text can be generated automatically

What protects the occupation

  • choosing the right objective, data and model-quality criteria
  • architecture decisions and production accountability
  • understanding business constraints and legacy systems
  • security and complex system integration

United States · before tax

Average pay and outlook

Estimated nominal monthly pay. The scenario reflects sector, demand and task resilience; it is not a guarantee of income.

2026$10 400per month
2035$13 200scenario estimate
2026: $10 40020262027: $10 70020272028: $10 95020282029: $11 25020292030: $11 55020302031: $11 85020312032: $12 20020322033: $12 50020332034: $12 85020342035: $13 2002035
Find jobs ↗The partner link may contain referral parameters. Data benchmark: U.S. Bureau of Labor Statistics ↗

Practical next step

Where to move next

Do not restart from zero: carry your experience forward and add scarce skills.

Data Analyst

Established resilient role
New role risk51%
DemandMediumDifficultyLowTime3–6 monthsSkill fit87%

AI Application Engineer

Established resilient role
New role risk19%
DemandHighDifficultyLowTime3–6 monthsSkill fit87%

AI Agent Supervisor

Emerging role
New role risk24%
DemandHighDifficultyLowTime3–6 monthsSkill fit85%

AI Evaluation Engineer

Emerging role
New role risk16%
DemandHighDifficultyLowTime3–6 monthsSkill fit83%

Analytics Engineer

Established resilient role
New role risk27%
DemandHighDifficultyLowTime3–6 monthsSkill fit81%

AI Security Engineer

Emerging role
New role risk14%
DemandHighDifficultyMediumTime6–12 monthsSkill fit64%

Job search and transitions

Find work with a lower risk index

Compare adjacent paths and open a current search for the selected occupation.

Skills you already have

  • data work
  • hypothesis testing
  • model-quality evaluation
  • systems thinking
  • software-system understanding
  • debugging

Skills to build

  • AI-system evaluation
  • model-behavior monitoring
  • AI governance
  • AI-agent-assisted development
  • architecture and system design
  • AI-generated code security
CurrentSpetsialist po mashinnomu obucheniyu (ml-inzhener) · 63%
→
Keepdata work · hypothesis testing · model-quality evaluation
→
AddAI-system evaluation · model-behavior monitoring · AI governance

Sources and update

Updated: 2026-09-26 · Assessment confidence: Medium

International Labour Organization · 2025Generative AI and Jobs: A Refined Global Index of Occupational Exposure

Nearly 30,000 tasks; a global assessment of GenAI exposure across detailed occupational groups.

World Economic Forum · 2025The Future of Jobs Report 2025

A survey of more than 1,000 employers representing over 14 million workers across 55 economies.

O*NET Resource Center · 2026O*NET Database

Occupational, task, skill and work-context structure.