Machine Learning Engineer in San Francisco — local hiring and talent graph insights
As of 2026-10-01, Skillenai has indexed 140 Machine Learning Engineer postings located in San Francisco over the past 90 days. The skill mentioned most often is Python, with demand up 6% vs the prior 4 weeks. The Skillenai talent graph adds career-history context: 407 of 2,172 observed Machine Learning Engineer career positions with documented skills mention python (18.7%). This sample covers all locations and years.
Last updated · 90d ending 2026-10-01
407 of 2,172 positions mention python (18.7%)
Career history · all locations · positions with documented skills
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Frequently asked questions about Machine Learning Engineer jobs in San Francisco
+Are Machine Learning Engineer jobs being posted in San Francisco right now?
Yes. Skillenai has indexed 140 Machine Learning Engineer postings located in San Francisco over the 90 days ending 2026-10-01, with demand up 6% vs the prior 4 weeks.
+What skills do Machine Learning Engineer jobs in San Francisco require?
Across Machine Learning Engineer postings in San Francisco indexed by Skillenai over the 90 days ending 2026-10-01, the skills mentioned most often are Python, machine learning, PyTorch, TensorFlow, SQL.
+Which other cities are hiring Machine Learning Engineer?
As of 2026-10-01, the metro areas posting the most Machine Learning Engineer jobs outside San Francisco are Mountain View, New York City, London, San Jose, Seattle, based on the Skillenai jobs index.
+How can I get notified about new Machine Learning Engineer jobs in San Francisco?
Skillenai sends a daily email digest of new Machine Learning 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 Machine Learning Engineer?
407 of 2,172 observed Machine Learning Engineer career positions with documented skills mention python (18.7%). 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 Machine Learning 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 Machine Learning Engineer in San Francisco?
The leading resolved employers in this page’s 90-day posting sample include Pinterest, CLERA, Together AI. The company table counts indexed postings, not hires, and links to published company pages where available.
Weekly Machine Learning Engineer postings in San Francisco — last 90 days
Skills most often required for Machine Learning Engineer in San Francisco
| Name | Postings | Share |
|---|---|---|
| Python | 82 | 58.6% |
| machine learning | 76 | 54.3% |
| PyTorch | 64 | 45.7% |
| TensorFlow | 44 | 31.4% |
| SQL | 33 | 23.6% |
| data pipelines | 30 | 21.4% |
| model evaluation | 29 | 20.7% |
| LLMs | 27 | 19.3% |
| feature engineering | 22 | 15.7% |
| deep learning | 21 | 15.0% |
| model training | 20 | 14.3% |
| Reinforcement learning | 19 | 13.6% |
Top companies posting Machine Learning Engineer jobs in San Francisco
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| 26 | |
| CLERA | 7 |
| Together AI | 5 |
| Discord | 4 |
| Checkr | 4 |
| European Tech Recruit | 3 |
| Handshake | 3 |
| OpenAI | 3 |
| Haus | 2 |
| Hive | 2 |
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 Machine Learning Engineer
| Name | Postings | Share |
|---|---|---|
| Mountain View | 136 | 97.1% |
| New York City | 102 | 72.9% |
| London | 101 | 72.1% |
| San Jose | 60 | 42.9% |
| Seattle | 56 | 40.0% |
| Santa Clara | 48 | 34.3% |
| Sunnyvale | 47 | 33.6% |
| Bengaluru | 42 | 30.0% |
| Toronto | 40 | 28.6% |
| Boston | 36 | 25.7% |
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 Machine Learning 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 |
|---|---|---|
| python | 407 of 2,172 | 18.7% |
| pytorch | 218 of 2,172 | 10.0% |
| tensorflow | 216 of 2,172 | 9.9% |
| scikit-learn | 144 of 2,172 | 6.6% |
| machine learning | 136 of 2,172 | 6.3% |
| docker | 133 of 2,172 | 6.1% |
| pandas | 109 of 2,172 | 5.0% |
| sql | 91 of 2,172 | 4.2% |
| xgboost | 90 of 2,172 | 4.1% |
| kubernetes | 89 of 2,172 | 4.1% |
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.
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-01, filtered to postings whose canonical role is “Machine Learning Engineer” and whose locationCity is “San Francisco”.
- city
- San Francisco
- role
- Machine Learning Engineer
- source
- Skillenai jobs index, deduplicated daily
- data_as_of
- 2026-10-01
- 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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