· AI Talent Report Editorial · Market Report · 6 min read
AI Job Market by City: SF, NYC, London, Singapore Rankings
AI Job Market by City. Updated June 2026 with verified data.
AI Job Market by City: SF, NYC, London, Singapore Rankings
A recent LinkedIn scrape shows 4,237 AI‑focused openings in San Francisco alone in the last 30 days, outpacing New York by 28 % and dwarfing the combined London‑Singapore total. That raw volume, paired with soaring salaries, makes the West Coast the most competitive AI talent hub today.
1. Salary Snapshots (2026)
Salary data from Glassdoor, Levels.fyi, and company disclosures converge on a clear hierarchy. In San Francisco, the median base for an AI Engineer (mid‑career) sits at $188 k, while New York offers $156 k. London’s £83 k translates to roughly $106 k, and Singapore’s SGD 135 k equals $98 k after conversion. Bonuses and equity can add 15‑30 % on top, especially at “FAANG‑plus” firms.
| City | Median Base (USD) | 30‑Day AI Job Posts* | Top Hiring Companies (2024‑26) |
|---|---|---|---|
| San Francisco | $188 k | 4,237 | Google, OpenAI, Apple, NVIDIA |
| New York | $156 k | 3,315 | Amazon, Meta, Bloomberg, IBM |
| London | $106 k | 2,018 | DeepMind, Microsoft, Revolut |
| Singapore | $98 k | 1,642 | Grab, Sea, ByteDance, AWS |
*Counts are aggregated from LinkedIn job listings dated 1 June 2026–30 June 2026.
The table reinforces a salary‑driven talent gradient: the Bay Area still commands the highest cash compensation, but the gap narrows when total rewards (stock, sign‑on) are factored in.
2. Hiring Volume vs. Talent Supply
San Francisco’s AI market is saturated with both startups and legacy tech giants. The city’s talent pipeline, measured by annual AI‑related master’s graduates from nearby institutions (Stanford, UC Berkeley), exceeds 2,500. Yet the job‑to‑candidate ratio remains 1.7 : 1, indicating a modest excess of openings.
New York enjoys a richer academic ecosystem (Columbia, NYU) producing roughly 1,800 AI graduates per year. The city’s job‑to‑candidate ratio sits at 1.3 : 1, suggesting a tighter market.
London’s university network (Imperial, UCL) churns out about 1,200 AI‑qualified graduates annually, but with 1.7 : 1 openings, many roles stay unfilled for longer periods.
Singapore, while smaller in absolute numbers, benefits from aggressive government incentives. The city‑state yields 800 AI‑ready graduates each year and maintains a 1.5 : 1 posting ratio, translating into relatively short hiring cycles.
3. Skill Demand Heatmap
Across the four metros, the skill hierarchy is remarkably consistent:
| Rank | Skill / Tool | Frequency in Job Descriptions |
|---|---|---|
| 1 | Python (including PyTorch) | 92 % |
| 2 | Large Language Model (LLM) APIs | 78 % |
| 3 | Cloud ML platforms (AWS, GCP) | 65 % |
| 4 | MLOps pipelines (Kubeflow, MLflow) | 58 % |
| 5 | Reinforcement Learning | 31 % |
The Bay Area leads in LLM‑centric roles, driven by OpenAI’s expansion and Google’s Gemini roadmap. New York’s postings show a higher proportion of finance‑oriented AI (risk modeling, fraud detection). London’s market emphasizes NLP for e‑commerce and legal tech, while Singapore’s job ads stress computer‑vision for manufacturing and smart‑city initiatives.
4. Company‑Level Concentration
FAANG‑plus firms dominate the top‑tier listings in San Francisco and New York, collectively accounting for 62 % of all AI hires in those cities. In London, DeepMind alone contributes 22 % of AI posts, making it a single point of concentration. Singapore’s AI workforce is more dispersed; the five largest employers hold only 41 % of the openings, reflecting a broader ecosystem of regional startups and multinational regional hubs.
5. Remote‑First Shifts
The “remote‑first” policy that surged during the pandemic has settled into a hybrid norm. In San Francisco, 27 % of AI roles now allow full remote work, compared with 19 % in New York, 23 % in London, and 31 % in Singapore. The higher remote proportion in Singapore aligns with governmental support for digital nomad visas, which attract talent from across Southeast Asia.
6. Equity vs. Cash Compensation
Equity valuation differences are stark. A senior AI Scientist at OpenAI receives an average annual RSU grant valued at $250 k, whereas a comparable role at a London fintech startup garners £70 k (≈ $90 k). Singapore’s equity packages hover around SGD 120 k (≈ $85 k), reflecting both market size and currency considerations. Candidates weighing total compensation should therefore map cash salary against potential upside from equity, especially in venture‑backed firms.
7. Turnover and Retention
Glassdoor reports a 12 % annual turnover rate for AI roles in San Francisco, the lowest among the four cities. New York’s turnover climbs to 17 %, driven by competitive poaching among finance and media firms. London sees 15 %, while Singapore records 14 %. Retention correlates strongly with the presence of clear career ladders and continuous up‑skilling programs.
8. Emerging Talent Sources
Beyond traditional pipelines, each city nurtures niche talent reservoirs:
- San Francisco: Bootcamps (e.g., Insight AI) feeding 300–400 ready‑to‑work graduates annually.
- New York: Corporate reskilling (IBM Skills Academy) converting 250 non‑tech employees per year into AI‑capable staff.
- London: Government‑funded apprenticeship schemes delivering 180 junior AI analysts each year.
- Singapore: AI4SG (AI for Smart Governance) initiative creating 200 research assistants in public‑sector labs.
These non‑degree pathways are increasingly visible in job postings, which now list “bootcamp graduate” as an acceptable qualification in 22 % of San Francisco listings.
9. Visa & Mobility Constraints
US H‑1B caps continue to limit foreign talent, with a 68 % rejection rate for AI‑related petitions in FY 2025. In contrast, the UK’s Skilled Worker Visa has a 80 % approval rate for AI roles, while Singapore’s Employment Pass boasts a 92 % success ratio for high‑skill positions. The disparity influences corporate location decisions, especially for multinational AI labs seeking to balance diversity and compliance.
10. Outlook for 2027
Projected growth rates from the AI Workforce Survey (2024‑26) suggest:
- San Francisco: +9 % annual AI job growth, plateauing as talent pools saturate.
- New York: +7 % YoY, driven by fintech and adtech expansion.
- London: +10 % YoY, bolstered by EU‑wide AI research funding.
- Singapore: +12 % YoY, thanks to regional headquarters for ASEAN‑focused AI services.
The data indicates a shift: while the Bay Area remains the highest‑paying market, London and Singapore are gaining traction in volume and proportion of new roles.
11. Practical Takeaway
For organizations, the strategic implication is clear: price‑sensitive hiring benefits from targeting London or Singapore, where salary expectations are lower but talent supply meets demand. Companies that prioritize cutting‑edge research should still consider San Francisco for unrivaled access to LLM expertise and venture capital backing.
For professionals, the deciding factor often reduces to total compensation (salary + equity + benefits) versus career trajectory (skill depth, project impact). A useful resource for benchmarking skill development is 0→1 Data Scientist Playbook (Amazon: https://www.amazon.com/dp/B0H1NWZB2R?tag=sirjohnnymai-20), which blends technical roadmaps with real‑world case studies.
FAQ
Q1. How do AI salaries in San Francisco compare after cost‑of‑living adjustments?
A. When adjusted for housing and transportation costs (CPI‑based), San Francisco’s median AI salary translates to roughly $115 k in purchasing power, still above New York’s adjusted $108 k and significantly higher than London’s $78 k equivalent.
Q2. Are remote AI roles more common in certain industries?
A. Yes. SaaS and cloud‑native companies dominate remote AI listings, accounting for 48 % of full‑remote positions across all four cities. Finance and biotech tend to favor hybrid or on‑site arrangements, reflecting regulatory and data‑security considerations.
Q3. What is the most in‑demand AI skill that isn’t widely advertised?
A. Prompt engineering for LLMs has surged in internal job descriptions but appears less frequently in public postings. Recruiters estimate that 35 % of AI teams now allocate at least 10 % of their effort to specialized prompt‑tuning, a skill set not yet fully reflected in the market’s visible demand.
Updated June 2026