distributed training jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-07-03, distributed training appears in 610 job postings indexed by Skillenai over the past 90 days — most often required for ML Engineer roles, with demand down 12% vs the prior 4 weeks.
Last updated · 90d ending 2026-07-03
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Frequently asked questions about distributed training
+Is distributed training in demand in 2026?
Yes. distributed training appears in 610 job postings indexed by Skillenai over the 90 days ending 2026-07-03, with demand down 12% vs the prior 4 weeks. It is most often required for ML Engineer roles (13% of ML Engineer postings list it).
+What jobs require distributed training?
According to the Skillenai jobs index over the 90 days ending 2026-07-03, the job titles most likely to require distributed training are ML Engineer (13% of postings list distributed training), Machine Learning Engineer (12% of postings list distributed training), Research Engineer (10% of postings list distributed training).
+What skills are commonly paired with distributed training?
Across job postings indexed by Skillenai (90 days ending 2026-07-03), distributed training most often appears alongside PyTorch, Python, machine learning, deep learning, JAX.
+Where is distributed training most in demand?
As of 2026-07-03, the metro areas posting the most jobs requiring distributed training are San Francisco, London, New York City, Palo Alto, San Jose, according to the Skillenai jobs index.
+How can I keep up with new distributed training content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning distributed training alongside the jobs index. You can subscribe to a daily email digest of new distributed training content from your Skillenai account.
Weekly job postings requiring distributed training — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Job titles most likely to require distributed training
| Role | Postings mentioning | % requiring |
|---|---|---|
| ML Engineer | 77 | 12.6% |
| Machine Learning Engineer | 73 | 12.0% |
| Research Engineer | 63 | 10.3% |
| Research Scientist | 41 | 6.7% |
| Software Engineer | 25 | 4.1% |
| ML Infrastructure Engineer | 17 | 2.8% |
| Applied Scientist | 15 | 2.5% |
| Machine Learning Researcher | 14 | 2.3% |
| Engineering Manager | 13 | 2.1% |
| AI Engineer | 10 | 1.6% |
Top metros hiring for distributed training
| Name | Postings | Share |
|---|---|---|
| San Francisco | 86 | 14.1% |
| London | 42 | 6.9% |
| New York City | 30 | 4.9% |
| Palo Alto | 26 | 4.3% |
| San Jose | 21 | 3.4% |
| Mountain View | 17 | 2.8% |
| Seattle | 11 | 1.8% |
| Beijing | 8 | 1.3% |
| Cambridge | 7 | 1.1% |
Skills commonly paired with distributed training
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-07-03. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Pages refresh weekly (or daily for the top-50 most-requested skills).
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- 286c07130d80afe5
- data_as_of
- 2026-07-03
- 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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