ML engineer (fintech) Salary in New York (2026): Complete Guide

ML engineer (fintech) salaries in New York in 2026 typically land between $145,000 and $320,000 base for most roles, with total compensation often reaching $180,000 to $450,000+ once bonus and equity are included. If you’re interviewing at a top-tier fintech or a well-funded trading/AI shop, principal-level packages can go higher.

Salary by Experience

New York pays a premium because it’s still one of the biggest hubs for fintech, banking, market-making, and risk systems. That concentration pushes compensation above what you’d see in most other US markets.

What Affects Your Salary

• •

  Fintech subdomain matters

  • •Fraud detection, credit risk, AML/KYC, pricing models, and trading ML usually pay more than generic recommendation or internal analytics work.
  • •Roles tied directly to revenue or regulatory risk tend to get bigger budgets.
• •

  Modeling depth changes your value

  • •If you can ship production ML systems end to end — feature pipelines, model monitoring, retraining, drift detection — you’ll command more than someone focused only on notebooks.
  • •Strong candidates who understand both modeling and software engineering usually get the upper end of the range.
• •

  Regulated industry premium

  • •Banks and insurance firms in New York pay for candidates who understand governance, auditability, explainability, and model risk management.
  • •If you’ve worked with SR 11-7-style controls or similar validation processes, that can move comp up meaningfully.
• •

  Company type drives the ceiling

  • •Large banks offer stability and strong bonuses but lower upside than hedge funds or high-growth fintechs.
  • •Trading firms and AI-heavy fintechs often pay the highest cash comp in exchange for stronger performance expectations.
• •

  Remote vs onsite can change the offer

  • •Fully remote roles may be priced against broader US bands unless the employer is firmly NYC-market anchored.
  • •Hybrid or onsite roles in Manhattan often keep compensation aligned with local market rates.

How to Negotiate

• •

  Anchor on total compensation, not just base

  • •In New York fintech, bonus can be a meaningful part of the package.
  • •Ask for the full structure: base salary, annual bonus target, sign-on bonus, equity vesting schedule, and any retention grants.
• •

  Quantify business impact in financial terms

  • •Don’t say “improved model performance.”
  • •Say “reduced fraud losses by $4.2M annually,” “cut manual review volume by 28%,” or “improved approval precision while keeping default rate flat.”
• •

  Use specialization as leverage

  • •If you’ve worked on credit scoring under regulatory constraints, transaction fraud at scale, or low-latency inference for trading workflows, say that clearly.
  • •Those are harder-to-hire skills than generic MLOps experience.
• •

  Negotiate based on scope as well as level

  • •In fintech interviews, title inflation is common. A “Senior ML Engineer” role may actually expect staff-level ownership.
  • •If you’re being asked to own roadmap decisions, cross-functional alignment, or production reliability across multiple teams, push for senior-principal compensation.

Comparable Roles

• •

  Data Scientist (Fintech)

  • •Typical NYC salary: $140,000–$250,000 base
  • •Usually pays slightly less than ML engineering unless it’s deeply product- or risk-oriented.
• •

  MLOps Engineer

  • •Typical NYC salary: $165,000–$260,000 base
  • •Strong overlap with ML engineer roles when infra ownership is central.
• •

  Applied Scientist / Research Scientist

  • •Typical NYC salary: $180,000–$300,000 base
  • •Higher if the role is research-heavy and tied to revenue-generating models.
• •

  Quantitative Developer / Quant ML Engineer

  • •Typical NYC salary: $220,000–$400,000+ base
  • •Often higher at hedge funds and prop trading firms than standard fintech companies.
• •

  Risk Modeler / Credit Model Developer

  • •Typical NYC salary: $150,,000–$240,,000 base
  • •Strong fit for banks and lenders; comp rises with regulatory ownership and portfolio impact.

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.