ML Infrastructure Engineer in San Francisco — local hiring and talent graph insights
As of 2026-10-29, Skillenai has indexed 10 ML Infrastructure Engineer postings located in San Francisco over the past 90 days. The skill mentioned most often is PyTorch. The Skillenai talent graph adds career-history context: 2 of 2 observed ML Infrastructure Engineer career positions with documented skills mention docker (100.0%). This sample covers all locations and years.
Last updated · 90d ending 2026-10-29
2 of 2 positions mention docker (100.0%)
Career history · all locations · positions with documented skills
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Frequently asked questions about ML Infrastructure Engineer jobs in San Francisco
+Are ML Infrastructure Engineer jobs being posted in San Francisco right now?
Yes. Skillenai has indexed 10 ML Infrastructure Engineer postings located in San Francisco over the 90 days ending 2026-10-29.
+What skills do ML Infrastructure Engineer jobs in San Francisco require?
Across ML Infrastructure Engineer postings in San Francisco indexed by Skillenai over the 90 days ending 2026-10-29, the skills mentioned most often are PyTorch, Kubernetes, distributed training, JAX, Distributed systems.
+Which other cities are hiring ML Infrastructure Engineer?
As of 2026-10-29, the metro areas posting the most ML Infrastructure Engineer jobs outside San Francisco are San Mateo, New York City, London, Mountain View, Beijing, based on the Skillenai jobs index.
+How can I get notified about new ML Infrastructure Engineer jobs in San Francisco?
Skillenai sends a daily email digest of new ML Infrastructure Engineer postings as they're indexed across the open web. Set up a saved search filtered to San Francisco from your account dashboard after creating a free Skillenai account.
+What do talent graph insights show about ML Infrastructure Engineer?
2 of 2 observed ML Infrastructure Engineer career positions with documented skills mention docker (100.0%). The Skillenai talent graph summarizes skills documented in career-profile positions across all locations and years. It complements the recent job-posting data on this page.
+What does the percentage in the career tables mean?
It is the number of observed career positions mentioning the skill divided by the number with at least one documented skill, multiplied by 100. For role rows, the denominator is positions in that role; for year rows, it is positions started that year. For example, 3 of 12 positions is 25%. Positions may mention multiple skills. These percentages describe the observed sample, not all workers, current vacancies, or the chance of getting a job.
+Are the career insights specific to San Francisco?
No. Career insights for ML Infrastructure Engineer cover all locations. Job postings, hiring companies, and required skills from postings on this page are filtered to San Francisco.
+Which companies are posting jobs for ML Infrastructure Engineer in San Francisco?
The leading resolved employers in this page’s 90-day posting sample include Physical Intelligence, Echo, Preference-Model. The company table counts indexed postings, not hires, and links to published company pages where available.
Weekly ML Infrastructure Engineer postings in San Francisco — last 90 days
Skills most often required for ML Infrastructure Engineer in San Francisco
| Name | Postings | Share |
|---|---|---|
| PyTorch | 7 | 70.0% |
| Kubernetes | 6 | 60.0% |
| distributed training | 5 | 50.0% |
| JAX | 4 | 40.0% |
| Distributed systems | 4 | 40.0% |
| CUDA | 4 | 40.0% |
| Ray | 3 | 30.0% |
| Python | 3 | 30.0% |
| Docker | 3 | 30.0% |
| checkpointing | 3 | 30.0% |
| vLLM | 3 | 30.0% |
| Megatron-LM | 2 | 20.0% |
Top companies posting ML Infrastructure Engineer jobs in San Francisco
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Physical Intelligence | 3 |
| Echo | 2 |
| Preference-Model | 1 |
| Character.AI | 1 |
| Abridge | 1 |
| GridCARE | 1 |
| Trajectory | 1 |
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.
Other top cities hiring ML Infrastructure Engineer
| Name | Postings | Share |
|---|---|---|
| San Mateo | 6 | 60.0% |
| New York City | 3 | 30.0% |
| London | 2 | 20.0% |
| Mountain View | 2 | 20.0% |
| Beijing | 1 | 10.0% |
| Cupertino | 1 | 10.0% |
| Palo Alto | 1 | 10.0% |
| Redwood City | 1 | 10.0% |
| Seattle | 1 | 10.0% |
| Seoul | 1 | 10.0% |
Skills mentioned in this role’s career histories
How often the listed skill is documented in career histories. Each row shows positions mentioning the listed skill out of all observed positions in ML Infrastructure Engineer with at least one documented skill. The percentage is that fraction × 100.
Skillenai talent graph · all locations · all observed years
| Skill | Positions mentioning skill / reviewed | % mentioning skill |
|---|---|---|
| docker | 2 of 2 | 100.0% |
| model inference | 1 of 2 | 50.0% |
| 3D reconstruction | 1 of 2 | 50.0% |
| Containerized ML workflows | 1 of 2 | 50.0% |
| Nvidia Jetson | 1 of 2 | 50.0% |
| EDGE devices | 1 of 2 | 50.0% |
| cuDNN | 1 of 2 | 50.0% |
| high-resolution imagery | 1 of 2 | 50.0% |
| ML infrastructure | 1 of 2 | 50.0% |
Career positions come from profile histories across all locations and years. Only positions with at least one documented skill are included. A position can mention several skills, so percentages do not add to 100%. These samples do not estimate the whole workforce or current hiring.
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 2026-10-29, filtered to postings whose canonical role is “ML Infrastructure Engineer” and whose locationCity is “San Francisco”.
- city
- San Francisco
- role
- ML Infrastructure Engineer
- source
- Skillenai jobs index, deduplicated daily
- data_as_of
- 2026-10-29
- window_days
- 90