recommendation systems jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-28, recommendation systems appears in 503 job postings indexed by Skillenai over the past 90 days — Machine Learning Engineer has the most postings mentioning recommendation systems, with demand down 50% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-28
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Frequently asked questions about recommendation systems
+Is recommendation systems in demand in 2026?
Yes. recommendation systems appears in 503 job postings indexed by Skillenai over the 90 days ending 2026-09-28, with demand down 50% vs the prior 4 weeks. Machine Learning Engineer accounts for the most postings mentioning recommendation systems (19.1% of all postings mentioning recommendation systems).
+What jobs require recommendation systems?
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 recommendation systems are Machine Learning Researcher (17.9% of that role’s postings mention recommendation systems), Applied AI Scientist (10.7% of that role’s postings mention recommendation systems), Applied ML Engineer (9.5% of that role’s postings mention recommendation systems).
+What skills are commonly paired with recommendation systems?
Across job postings indexed by Skillenai (90 days ending 2026-09-28), recommendation systems most often appears alongside machine learning, Python, experimentation, personalization, A/B testing.
+Where is recommendation systems most in demand?
As of 2026-09-28, the metro areas posting the most jobs requiring recommendation systems are San Francisco, New York City, London, Bengaluru, San Jose, according to the Skillenai jobs index.
+How can I keep up with new recommendation systems content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning recommendation systems alongside the jobs index. You can subscribe to a daily email digest of new recommendation systems content from your Skillenai account.
Weekly job postings requiring recommendation systems — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Roles most likely to require recommendation systems
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Machine Learning Researcher | 7 | 17.9% |
| Applied AI Scientist | 3 | 10.7% |
| Applied ML Engineer | 2 | 9.5% |
| Applied Data Scientist | 4 | 9.3% |
| Machine Learning Manager | 2 | 8.7% |
| ML Engineering Manager | 2 | 8.3% |
| Delivery Manager | 1 | 5.0% |
| Technology Product Manager | 1 | 5.0% |
| Founding AI Engineer | 1 | 4.5% |
| Field Engineer | 2 | 4.4% |
Roles with the most recommendation systems postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Machine Learning Engineer | 96 | 19.1% |
| Product Manager | 72 | 14.3% |
| Data Scientist | 68 | 13.5% |
| Software Engineer | 43 | 8.5% |
| ML Engineer | 17 | 3.4% |
| AI Engineer | 12 | 2.4% |
| Engineering Manager | 8 | 1.6% |
| Technical Program Manager | 8 | 1.6% |
| Machine Learning Researcher | 7 | 1.4% |
| AI/ML Engineer | 6 | 1.2% |
Top metros hiring for recommendation systems
| Name | Postings | Share |
|---|---|---|
| San Francisco | 43 | 8.5% |
| New York City | 32 | 6.4% |
| London | 24 | 4.8% |
| Bengaluru | 15 | 3.0% |
| San Jose | 14 | 2.8% |
| Austin | 7 | 1.4% |
| Mountain View | 7 | 1.4% |
| Seattle | 7 | 1.4% |
| Toronto | 7 | 1.4% |
Skills commonly paired with recommendation systems
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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 recommendation systems by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s recommendation systems postings by all recommendation systems 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
- ad28684d3b45ce0d
- 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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