TensorRT-LLM jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, TensorRT-LLM appears in 210 job postings indexed by Skillenai over the past 90 days — Machine Learning Engineer has the most postings mentioning TensorRT-LLM, with demand share up 1.7% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about TensorRT-LLM
+Is TensorRT-LLM in demand in 2026?
Yes. TensorRT-LLM appears in 210 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Machine Learning Engineer accounts for the most postings mentioning TensorRT-LLM (14.3% of all postings mentioning TensorRT-LLM).
+What jobs require TensorRT-LLM?
According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning TensorRT-LLM are ML Platform Engineer (27.1% of that role’s postings mention TensorRT-LLM), Machine Learning Platform Engineer (16.7% of that role’s postings mention TensorRT-LLM), AI Infrastructure Engineer (11.4% of that role’s postings mention TensorRT-LLM).
+What skills are commonly paired with TensorRT-LLM?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), TensorRT-LLM most often appears alongside vLLM, SGLang, Python, PyTorch, CUDA.
+Where is TensorRT-LLM most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring TensorRT-LLM are San Francisco, Singapore, San Jose, Santa Clara, Palo Alto, according to the Skillenai jobs index.
+How can I keep up with new TensorRT-LLM content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning TensorRT-LLM alongside the jobs index. You can subscribe to a daily email digest of new TensorRT-LLM content from your Skillenai account.
+Which skills come before and after TensorRT-LLM?
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 TensorRT-LLM — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around TensorRT-LLM
Skills documented before and after this skill across employer changes.
Not enough linked career history to draw this chart yet.
Roles most likely to require TensorRT-LLM
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| ML Platform Engineer | 13 | 27.1% |
| Machine Learning Platform Engineer | 4 | 16.7% |
| AI Infrastructure Engineer | 8 | 11.4% |
| Tech Lead Manager | 2 | 9.1% |
| Developer Relations Manager | 3 | 8.6% |
| AI Research Intern | 2 | 8.3% |
| ML Systems Engineer | 3 | 7.3% |
| Machine Learning Infrastructure Engineer | 2 | 6.2% |
| ML Ops Engineer | 2 | 4.9% |
| AI/ML Architect | 1 | 3.8% |
Roles with the most TensorRT-LLM postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Machine Learning Engineer | 30 | 14.3% |
| Software Engineer | 29 | 13.8% |
| Solutions Architect | 15 | 7.1% |
| ML Platform Engineer | 13 | 6.2% |
| AI Infrastructure Engineer | 8 | 3.8% |
| Forward Deployed Engineer | 6 | 2.9% |
| Research Engineer | 6 | 2.9% |
| Inference Engineer | 4 | 1.9% |
| ML Engineer | 4 | 1.9% |
| Machine Learning Platform Engineer | 4 | 1.9% |
Top companies posting jobs requiring TensorRT-LLM
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| NVIDIA | 35 |
| Bjakcareer | 15 |
| Together AI | 10 |
| Nebius | 8 |
| Inferact | 5 |
| Advanced Micro Devices Inc. | 4 |
| Netskope | 4 |
| Grab | 4 |
| Baseten | 4 |
| Monolith | 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 TensorRT-LLM
| Name | Postings | Share |
|---|---|---|
| San Francisco | 28 | 13.3% |
| Singapore | 16 | 7.6% |
| San Jose | 12 | 5.7% |
| Santa Clara | 12 | 5.7% |
| Palo Alto | 8 | 3.8% |
| London | 7 | 3.3% |
| Seoul | 5 | 2.4% |
| Shanghai | 5 | 2.4% |
| Bellevue | 4 | 1.9% |
Skills commonly paired with TensorRT-LLM
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. 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 TensorRT-LLM by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s TensorRT-LLM postings by all TensorRT-LLM 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). Adjusted posting share: 0.1% to 0.1%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,595 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- 89a53ba9c95a032f
- data_as_of
- 2026-09-30
- 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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