Machine learning and AI engineer resume keywords

We counted the skills in 868 open machine learning and AI engineer job postings from 166 employers, including Waymo, OpenAI and Anthropic. The ones employers ask for most are machine learning (82% of postings), AI (77%) and LLMs (44%).

Top skills and tools in machine learning and AI engineer postings

#KeywordShare of postings
1machine learning 82%
2AI 77%
3LLMs 44%
4Python 43%
5deep learning 24%
6prototyping 21%
7A/B testing 21%
8PyTorch 20%
9product roadmap 20%
10APIs 19%
11algorithms 17%
12generative AI 17%
13automation 17%
14observability 17%
15backend 12%
16sales 11%
17AWS 11%
18computer vision 10%
19robotics 10%
20shipping 10%
21TensorFlow 10%
22UX 9%
23statistics 9%
24C++ 9%
25RAG 9%
26NLP 9%
27distributed systems 8%
28data pipelines 8%
29MLOps 8%
30Apache Spark 8%

Share of the 868 postings whose description names the skill (plurals and common spellings, such as “JS” and “JavaScript”, count as one).

Soft skills employers mention

leadership · 10%ownership · 9%communication · 9%collaboration · 8%cross-functional · 6%decision making · 5%

Show these through results in your bullets (“led a team of six”) rather than listing them as adjectives.

How to use these keywords on your machine learning and AI engineer resume

  1. Start with the posting, not this list. These are averages across 868 jobs; the one you're applying for has its own priorities. Use this page to spot common gaps, then match the specific posting.
  2. Name skills the way employers do. If you use “machine learning”, “AI” and “LLMs”, write those exact words. Applicant tracking systems and recruiters search for them, and a close synonym can be missed.
  3. Put each skill in a bullet that shows a result. Naming Python inside a bullet about what you achieved with it, with a number where you can, is stronger than listing it alone in a skills section.
  4. Add only what's true. If you've worked with “Python”, “deep learning” and “prototyping” but your resume doesn't say so, add it. If you haven't, leave it out: interviews expose padded resumes quickly.

How these numbers are calculated

Every figure comes from open machine learning and AI engineer job postings on MANY Hired, imported from employers' own career pages. For each posting we pick out the skills, tools, certifications and qualifications its description names, then count how many postings ask for each one. A job counts as machine learning and AI engineer by its title. Updated October 28, 2026.