benchmarks jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-11-06, benchmarks appears in 246 job postings indexed by Skillenai over the past 90 days — Research Engineer has the most postings mentioning benchmarks.
Last updated · 90d ending 2026-11-06
Which roles want benchmarks?
Upload your resume and Skillenai will show which roles your benchmarks experience fits, which skills you already cover, and what is missing.
Frequently asked questions about benchmarks
+Is benchmarks in demand in 2026?
Yes. benchmarks appears in 246 job postings indexed by Skillenai over the 90 days ending 2026-11-06. Research Engineer accounts for the most postings mentioning benchmarks (20.7% of all postings mentioning benchmarks).
+What jobs require benchmarks?
According to the Skillenai jobs index over the 90 days ending 2026-11-06, among roles with at least 20 postings, the highest shares mentioning benchmarks are Storage Architect (8.7% of that role’s postings mention benchmarks), Research Engineer (7.5% of that role’s postings mention benchmarks), IT Consultant (4.8% of that role’s postings mention benchmarks).
+What skills are commonly paired with benchmarks?
Across job postings indexed by Skillenai (90 days ending 2026-11-06), benchmarks most often appears alongside Python, Reinforcement learning, evaluation frameworks, machine learning, Docker.
+Where is benchmarks most in demand?
As of 2026-11-06, the metro areas posting the most jobs requiring benchmarks are San Francisco, Singapore, London, New York City, Amsterdam, according to the Skillenai jobs index.
+How can I keep up with new benchmarks content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning benchmarks alongside the jobs index. You can subscribe to a daily email digest of new benchmarks content from your Skillenai account.
+Which skills come before and after benchmarks?
The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.
Weekly indexed postings requiring benchmarks — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around benchmarks
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before benchmarks
Skills after benchmarks
How to read this chart · view counts
Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.
The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.
Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.
| Connection | Moves |
|---|---|
| Before: retrain embedding models | 1 |
| Before: metric learning | 1 |
| Before: mobile deployment | 1 |
| Before: prompting techniques | 1 |
| Before: docker | 1 |
| Before: Kubernetes (cluster) | 1 |
| Before: kubernetes | 1 |
| Before: open-source resource | 1 |
| After: roadmap planning | 1 |
| After: BLE connectivity | 1 |
| After: SoCs | 1 |
| After: product | 1 |
| After: product certification | 1 |
| After: Alexa Gadgets (BLE) | 1 |
| After: Panels | 1 |
| After: Training sessions | 1 |
Roles most likely to require benchmarks
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Storage Architect | 2 | 8.7% |
| Research Engineer | 51 | 7.5% |
| IT Consultant | 1 | 4.8% |
| AI Manager | 1 | 4.5% |
| AI Systems Architect | 1 | 4.0% |
| AI Researcher | 4 | 3.5% |
| AI Technical Lead | 1 | 3.3% |
| AI Security Researcher | 1 | 3.1% |
| Data Science Engineer | 1 | 3.1% |
| Technology Consultant | 1 | 2.8% |
Roles with the most benchmarks postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Research Engineer | 51 | 20.7% |
| Software Engineer | 22 | 8.9% |
| AI Engineer | 16 | 6.5% |
| Machine Learning Engineer | 13 | 5.3% |
| Applied AI Engineer | 7 | 2.8% |
| Product Manager | 6 | 2.4% |
| ML Engineer | 5 | 2.0% |
| Research Scientist | 5 | 2.0% |
| AI Researcher | 4 | 1.6% |
| AI Safety Red Team Expert | 4 | 1.6% |
Top companies posting jobs requiring benchmarks
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| CLERA | 51 |
| OpenBrain | 14 |
| Wavestone | 10 |
| Anthropic | 7 |
| Turing | 5 |
| Artefact | 4 |
| ServiceNow | 4 |
| Autodesk | 3 |
| Teradata | 3 |
| Shield34 | 3 |
Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.
Top metros hiring for benchmarks
| Name | Postings | Share |
|---|---|---|
| San Francisco | 35 | 14.2% |
| Singapore | 22 | 8.9% |
| London | 10 | 4.1% |
| New York City | 10 | 4.1% |
| Amsterdam | 7 | 2.8% |
| Puteaux | 7 | 2.8% |
| Mountain View | 4 | 1.6% |
| Munich | 4 | 1.6% |
| Bengaluru | 3 | 1.2% |
Skills commonly paired with benchmarks
Explore related pages
How this was computed
Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-11-06. 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 benchmarks by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s benchmarks postings by all benchmarks 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). An adjusted trend is not shown because comparable posting coverage is insufficient.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- e97e25fffb0d7cba
- data_as_of
- 2026-11-06
- window_days
- 90