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AI Architect vs ML Engineer: what energy employers ask for

As of 29 October 2026, Plutarch tracked 75 open AI Architect postings and 77 open ML Engineer postings at energy employers.

Skills and tools

Share of the postings we could read in full that name each skill: 57 for AI Architect, 71 for ML Engineer.

Skills named in AI Architect and ML Engineer postings.
Skill or toolAI ArchitectML Engineer
Machine learning33%87%
Python42%86%
AI agents61%28%
Azure61%35%
PyTorchnot listed55%
Generative AI49%not listed
MLOps33%49%
AWS35%46%
LLMs44%46%
RAG46%not listed
CI/CD23%34%
SQL30%34%
Deep learningnot listed30%
Dockernot listed30%
Statisticsnot listed30%
Gitnot listed28%
TensorFlownot listed27%
Cybersecurity26%not listed
Google Cloud26%not listed
Agile / Scrum19%not listed
DevOps18%not listed

Where the postings are

Countries of open AI Architect and ML Engineer postings, as a share of each role's postings.
CountryAI ArchitectML Engineer
United States40%43%
India15%12%
United Kingdomnot listed10%
Canada8%not listed
Chinanot listed5%
Australianot listed4%
Germany4%not listed
Norway4%not listed

How many postings state pay

  • AI Architect: 11 of 43 postings whose pay we could read (26%)
  • ML Engineer: 24 of 53 postings whose pay we could read (45%)

Pay levels are not compared here: each role's figures come from different countries and currencies. They are on each role's own page. Pay disclosure tracks local pay-transparency law more closely than employer policy, so the two rates partly reflect where each role is advertised.

“Not listed” means the skill, credential or country is not among those shown on that role's own page, not that no posting names it. This compares what employers ask for in the two roles; it does not count how many people hold those skills or say that one role can do the other.

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