How do you hire a machine learning engineer for a technology company?

In short

Hire a machine learning engineer who can frame a business or technical problem as a model a computer can solve, and judge whether the project is feasible before building it. Computer and Information Research Scientists, the closest O*NET occupation, lists formulating mathematical models of problems for solution by computers and assessing the feasibility of project plans among its core tasks.

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What does a machine learning engineer do day to day at a technology company?

O*NET has no machine learning engineer occupation. The closest O*NET occupation is Computer and Information Research Scientists (O*NET 15-1221.00), and its core tasks include:

The O*NET list covers problem framing and research. Write the production duties, such as deploying and monitoring models, from your own team's work.

  • Analyze problems to develop solutions involving computer hardware and software.
  • Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.
  • Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers.
  • Evaluate project plans and proposals to assess feasibility issues.
  • Consult with users, management, vendors, and technicians to determine computing needs and system requirements.
  • Meet with managers, vendors, and others to solicit cooperation and resolve problems.

Which skills should a machine learning engineer job description ask for?

A machine learning engineer job description should ask for a problem the candidate turned into a model, the measure they chose to judge it, and why the approach was feasible with the data available.

O*NET's technology list for Computer and Information Research Scientists includes Apache Airflow, Apache Hadoop, Apache Hive, Amazon Redshift and Amazon DynamoDB, all data infrastructure tools. Name the modelling frameworks your team uses separately, since the list does not cover them.

  • Framed a vague business problem as a model with a stated objective
  • Turned down or reshaped a project after a feasibility check
  • Worked with users or managers to set the system requirements
  • Explained a model's limits to people outside the team

Which titles do machine learning engineer candidates use?

Machine learning engineer candidates often carry research titles. The titles O*NET reports for Computer and Information Research Scientists are Computer Scientist, Computer Specialist, Control System Computer Scientist, Research Scientist and Scientific Programmer Analyst. Search for Machine Learning Engineer by name as well, because O*NET does not list it for this occupation.

How much of a machine learning engineer's work do people bring to AI tools?

0.08% of sampled Claude.ai conversations in May 2026 were about the tasks of Computer and Information Research Scientists, the closest O*NET occupation, according to the Anthropic Economic Index. In those conversations, 57.93% asked Claude to complete the task directly (automation) and 42.07% worked with it iteratively (augmentation).

Computer and Information Research Scientists is one of the occupations where automation outweighed augmentation in that sample. For hiring, ask how the candidate verifies code or analysis an assistant produced before trusting a model built on it. The figures describe how people used Claude, not how many machine learning jobs exist.

Common questions

Should you hire a machine learning engineer or a data scientist?
Hire a data scientist when the work is analysing data and validating models to inform decisions, and a machine learning engineer when a model must run inside a product. O*NET has an occupation for Data Scientists but none for machine learning engineers.
Which O*NET occupation is closest to a machine learning engineer?
Computer and Information Research Scientists (O*NET 15-1221.00) is the closest O*NET occupation. Data Scientists is the alternative when the role is mostly analysis.

Where this data comes from

  • O*NET 31.0 DatabaseThis page includes information from the O*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. EmployLabs has modified all or some of this information. USDOL/ETA has not approved, endorsed, or tested these modifications.
  • Anthropic Economic Index, release_2026_06_26 (claude_ai, global, soc_occupation, May 2026)Anthropic Economic Index (Anthropic), data released under CC BY. Usage share is the share of sampled Claude.ai conversations classified to this occupation; the automation/augmentation split describes how those conversations used Claude. Neither measures the labour market.

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