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

ML engineer (insurance) salaries in New York in 2026 typically land between $140,000 and $260,000 base, with total compensation often reaching $170,000 to $350,000+ when bonus and equity are included. If you’re working on production ML for underwriting, pricing, claims automation, or fraud detection at a top insurer or insurtech, the upper end moves fast.

Salary by Experience

New York pays a premium because it’s a dense market for insurance carriers, brokers, reinsurers, and insurtechs. That matters: insurance firms in New York often compete with fintech and big tech-adjacent employers for the same ML talent.

What Affects Your Salary

• •

  Insurance domain depth

  • •If you’ve shipped models for pricing, loss prediction, claims triage, fraud detection, or catastrophe risk, you’re worth more than a generalist ML engineer.
  • •Insurance-specific experience reduces ramp time and lowers model governance risk.
• •

  Production ML + MLOps

  • •Engineers who can build training pipelines, feature stores, monitoring, drift detection, and retraining workflows get paid above pure research profiles.
  • •In insurance, “works in notebook” is not enough. Teams want auditability and repeatability.
• •

  Regulated environment experience

  • •Familiarity with model risk management, explainability requirements, fairness testing, and documentation pushes compensation up.
  • •New York insurers care about governance because models affect underwriting decisions and pricing outcomes.
• •

  Company type

  • •Large carriers usually pay strong cash comp plus bonus.
  • •Insurtechs may offer slightly lower base but better equity upside.
  • •Reinsurers and specialty lines firms often pay more for niche actuarial/ML crossover skills.
• •

  Work location

  • •Onsite or hybrid roles in Manhattan often pay more than fully remote roles tied to lower-cost geographies.
  • •Some firms will discount remote comp if the role is not anchored to New York labor market rates.

How to Negotiate

• •

  Anchor your ask to insurance outcomes

  • •Don’t lead with generic ML metrics. Lead with business impact:
    • •reduced claims handling time
    • •improved loss ratio
    • •lower fraud false positives
    • •better quote conversion
  • •Hiring managers in insurance respond to measurable underwriting or claims impact.
• •

  Price in your governance experience

  • •If you’ve worked with model validation teams, legal/compliance review, or adverse action constraints, call that out explicitly.
  • •That experience is hard to find and saves the company from downstream rework.
• •

  Separate base from total comp

  • •In New York insurance roles, base salary is only one part of the package.
  • •Negotiate:
    • •signing bonus
    • •annual bonus target
    • •equity or LTIP
    • •relocation support
    • •education budget for cloud/ML certs
• •

  Use market anchors from adjacent roles

  • •If the company lowballs the title “ML engineer,” compare it against:
    • •senior data scientist
    • •applied scientist
    • •MLOps engineer
    • •quantitative analytics engineer
  • •Insurance companies often blur these titles. Push for compensation based on scope, not label.

Comparable Roles

• •

  Data Scientist (Insurance) — $135,000–$220,000 base

  • •Usually closer to analytics/modeling than full production engineering.
• •

  Applied Scientist — $180,000–$270,000 base

  • •Often higher if the role includes advanced modeling or experimentation at scale.
• •

  MLOps Engineer — $175,000–$260,000 base

  • •Strong benchmark if your work includes deployment pipelines and monitoring.
• •

  Quantitative Analyst / Risk Modeler — $160,000–$250,000 base

  • •Common in pricing/reserving/risk functions inside insurers and reinsurers.
• •

  Senior Software Engineer (AI/Platform) — $170,000–$240,000 base

  • •Useful comparison if your role is more infrastructure-heavy than modeling-heavy.

If you’re interviewing in New York insurance right now, treat anything below $170k base for a mid-level ML engineer as weak unless the role has exceptional equity or unusually strong growth potential. For senior candidates with real insurance ML delivery experience، the market supports a much higher number.

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.