Hiring a machine learning engineer in San Francisco? Across 664 live machine learning engineer postings in San Francisco, the market pays a $232K median salary (typically $200K–$270K). Recruiting from Scratch is the contingency technical recruiting firm for these hires — a 29-day average time to hire, 300+ placements, and a 2M+ candidate network.
A machine learning engineer builds, trains, and deploys machine-learning models and the production systems that serve them. Hiring one in San Francisco means competing with the companies below.
What employers actually screen for, aggregated across 664 active machine learning engineer postings in San Francisco:
| Percentile | Base salary |
|---|---|
| 25th | $200K |
| Median | $232K |
| 75th | $270K |
Based on 428 machine learning engineer postings in San Francisco that disclose pay. Base only — equity is typically on top.
San Francisco pays about 14% above the US median for this role ($203K).
Across the 344 machine learning engineer postings in San Francisco that spell out responsibilities:
The companies with the most live machine learning engineer openings in San Francisco, with what each pays and screens for (medians shown only where at least 3 postings disclose pay):
| Company | Open machine learning engineer roles | Median pay (disclosed) | Top skills |
|---|---|---|---|
| Waymo | 39 | $238K | Python, PyTorch, TensorFlow |
| Apple | 33 | — | Python, PyTorch, TensorFlow |
| ServiceNow | 20 | $218K | Python, Go, Hugging Face |
| 15 | $290K | SQL, Python, Java | |
| Uber | 14 | — | PyTorch, Python, TensorFlow |
| Roblox | 11 | $285K | Data Pipelines, AWS, GCP |
| Tesla | 11 | — | — |
| General Motors | 10 | $245K | Python, PyTorch, TypeScript |
| Stealth Startup | 9 | $225K | — |
| Rivian | 8 | $257K | Python, PyTorch |
Where the machine learning engineer demand sits across funding stages, across the 150 companies with the most live openings in San Francisco:
| Stage | Companies hiring | Open roles | Median pay (disclosed) | Examples |
|---|---|---|---|---|
| Seed | 21 | 59 | $215K | Uber, Atoms, Clera |
| Series A | 10 | 20 | $213K | Orchard Robotics, Chef Robotics, Maven Robotics |
| Series B | 12 | 31 | $225K | Reducto, Lightfield, Krea |
| Series C | 8 | 20 | $245K | NewsBreak, Latent, Together Ai |
| Series D+ | 37 | 137 | $250K | Waymo, Scale AI, Glean |
| Public | 28 | 157 | $242K | Apple, ServiceNow, Pinterest |
A further 34 of those companies have no funding stage on file and are not shown above.
Recruiting from Scratch is a contingency technical recruiting firm — no retainer and no upfront cost, so you pay only when you make a hire. The process: align on the role and must-haves → a curated shortlist of 3–5 genuinely qualified machine learning engineers (not resume volume) → a 29-day average time to hire versus the 49-day industry average → a 90-day replacement guarantee. Backed by 300+ placements, a 2M+ candidate network, and named hires at companies like Decagon and Mercor.
A machine learning engineer builds, trains, and deploys machine-learning models and the production systems that serve them.
What salary does a machine learning engineer in San Francisco command in 2026?Across 664 live postings in San Francisco, a $232K median salary (typically $200K–$270K) — base only; equity is typically on top. Most postings expect 5+ years of experience.
What should you look for when hiring a machine learning engineer?Depth in the skills these postings require (Python, PyTorch, TensorFlow, AWS, data pipelines, Kubernetes, GCP, Go), plus ML fundamentals paired with real production engineering — not just notebooks. Recruiting from Scratch sends a shortlist of 3–5 genuinely qualified candidates, not resume volume.
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