ranking jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-28, ranking appears in 463 job postings indexed by Skillenai over the past 90 days — Machine Learning Engineer has the most postings mentioning ranking, with demand down 5% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-28
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Frequently asked questions about ranking
+Is ranking in demand in 2026?
Yes. ranking appears in 463 job postings indexed by Skillenai over the 90 days ending 2026-09-28, with demand down 5% vs the prior 4 weeks. Machine Learning Engineer accounts for the most postings mentioning ranking (23.5% of all postings mentioning ranking).
+What jobs require ranking?
According to the Skillenai jobs index over the 90 days ending 2026-09-28, among roles with at least 20 postings, the highest shares mentioning ranking are Machine Learning Manager (21.7% of that role’s postings mention ranking), Agent Engineer (14.3% of that role’s postings mention ranking), Applied ML Engineer (14.3% of that role’s postings mention ranking).
+What skills are commonly paired with ranking?
Across job postings indexed by Skillenai (90 days ending 2026-09-28), ranking most often appears alongside machine learning, Python, Retrieval, experimentation, recommendation systems.
+Where is ranking most in demand?
As of 2026-09-28, the metro areas posting the most jobs requiring ranking are San Francisco, New York City, Seattle, Amsterdam, London, according to the Skillenai jobs index.
+How can I keep up with new ranking content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning ranking alongside the jobs index. You can subscribe to a daily email digest of new ranking content from your Skillenai account.
Weekly job postings requiring ranking — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Roles most likely to require ranking
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Machine Learning Manager | 5 | 21.7% |
| Agent Engineer | 3 | 14.3% |
| Applied ML Engineer | 3 | 14.3% |
| Applied Research Engineer | 2 | 8.0% |
| Principal Data Scientist | 3 | 7.7% |
| Machine Learning Engineering Manager | 4 | 6.8% |
| Machine Learning Scientist | 7 | 5.1% |
| Machine Learning Engineer | 109 | 4.8% |
| Back End Engineer | 1 | 4.8% |
| Applied Data Scientist | 2 | 4.7% |
Roles with the most ranking postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Machine Learning Engineer | 109 | 23.5% |
| Software Engineer | 57 | 12.3% |
| Product Manager | 56 | 12.1% |
| Data Scientist | 35 | 7.6% |
| Engineering Manager | 20 | 4.3% |
| AI Engineer | 10 | 2.2% |
| ML Engineer | 10 | 2.2% |
| Machine Learning Scientist | 7 | 1.5% |
| Technical Product Manager | 7 | 1.5% |
| Technical Program Manager | 7 | 1.5% |
Top metros hiring for ranking
| Name | Postings | Share |
|---|---|---|
| San Francisco | 51 | 11.0% |
| New York City | 26 | 5.6% |
| Seattle | 14 | 3.0% |
| Amsterdam | 13 | 2.8% |
| London | 12 | 2.6% |
| Toronto | 12 | 2.6% |
| Mountain View | 11 | 2.4% |
| San Jose | 11 | 2.4% |
| Austin | 9 | 1.9% |
Skills commonly paired with ranking
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-28. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning ranking by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s ranking postings by all ranking postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills).
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- 763204149e819c5b
- data_as_of
- 2026-09-28
- window_days
- 90
The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.
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