The convergence of artificial intelligence and financial services has created one of the most dynamic job markets in the global economy. From JPMorgan deploying large language models to parse regulatory filings, to Citadel and Two Sigma building proprietary ML pipelines for alpha generation, to Stripe and Plaid using deep learning for real-time fraud detection — every corner of finance is being reshaped by AI.
AI finance jobs span a remarkably wide spectrum. On the technical side, machine learning engineers build credit-risk models at Capital One, quantitative researchers develop systematic trading strategies at D.E. Shaw, and data scientists train NLP systems for sentiment analysis at Bloomberg. On the business side, AI strategy leads at Goldman Sachs define enterprise adoption roadmaps, product managers at Ramp shape AI-powered expense tools, and compliance officers at Moody's design frameworks for responsible AI in credit ratings.
This job board exists for both audiences. If you are a finance professional — an analyst, portfolio manager, or risk officer — looking to pivot toward AI-oriented roles, you will find transition-friendly positions that value your domain expertise. If you are an ML engineer, data scientist, or researcher looking to apply your technical skills in financial services, you will find roles at hedge funds, banks, insurers, and fintechs that need exactly your skillset. We curate every listing by hand, verify that each URL is live, and tag roles with editorial context so you can quickly find the right fit.
Frequently Asked Questions
- What are AI finance jobs?
- AI finance jobs are roles that sit at the intersection of artificial intelligence and financial services. They include machine learning engineers building fraud-detection models at banks, data scientists developing credit-risk algorithms at fintechs, AI strategists leading enterprise adoption at asset managers, and finance professionals (FP&A, corporate development, investor relations) working at AI companies like Anthropic, OpenAI, or CoreWeave. The common thread is that every role requires fluency in both AI/ML concepts and financial domain knowledge.
- What skills do I need for AI finance jobs?
- The required skills depend on which side of the intersection you approach from. Technical roles (ML engineering, data science, quant research) typically require Python, SQL, experience with frameworks like PyTorch or TensorFlow, and knowledge of financial instruments or markets. Business-side roles (AI strategy, AI product management, compliance) value domain expertise in banking, insurance, or capital markets combined with an understanding of ML workflows, model risk, and data governance. Many roles explicitly seek candidates who can translate between technical and business stakeholders — a skill that is hard to hire for and commands a premium.
- What salaries can I expect in AI finance?
- Compensation in AI finance is among the highest in tech or finance individually. Junior ML engineers at major banks typically earn $120K-$180K total compensation. Senior data scientists at hedge funds like Citadel or Two Sigma can earn $250K-$500K+. Strategic finance roles at well-funded AI companies (Anthropic, Scale AI, CoreWeave) range from $150K-$300K depending on seniority. Quantitative researchers at top firms often exceed $400K at mid-career. Salaries vary significantly by location, company type, and specialization — we include verified salary ranges on listings where available.
- Are there remote AI finance jobs?
- Yes, and the number is growing. Fintechs and AI startups tend to be the most remote-friendly — companies like Ramp, Mercury, and many AI infrastructure firms hire distributed teams. Traditional banks and hedge funds are more likely to require hybrid or onsite presence, especially for roles involving proprietary trading systems or sensitive data. We tag every listing with its remote policy (remote, hybrid, or onsite) so you can filter accordingly. Browse our dedicated remote AI finance jobs page for the full list of location-flexible roles.
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