ML engineer (fintech) Salary in Stockholm (2026): Complete Guide

ML engineer (fintech) salaries in Stockholm in 2026 typically land between $62,000 and $185,000 USD base depending on seniority, with total comp going higher at banks, payment companies, and well-funded fintechs. For a strong mid-level candidate, $88,000 to $120,000 USD is the most realistic negotiating band.

Salary by Experience

Stockholm pays well by European standards, but fintech usually adds a premium over general software roles. If you are working on fraud detection, credit risk, AML automation, or real-time decisioning, expect the upper half of these ranges.

What Affects Your Salary

• •

  Domain specialization matters more than generic ML experience.

  • •Fraud detection, anti-money laundering, credit scoring, risk modeling, and recommender systems for financial products pay better than broad “ML platform” work.
  • •If you can show measurable lift in approval rates, fraud reduction, or loss-rate improvement, your comp moves up fast.
• •

  Fintech pays differently from traditional enterprise tech.

  • •Stockholm has a strong concentration of banks and financial services alongside fintech startups.
  • •The biggest premium usually comes from regulated financial products where model quality directly impacts revenue or regulatory exposure.
• •

  Remote flexibility can cut both ways.

  • •Fully remote roles sometimes benchmark against broader Nordic or EU markets and may pay slightly less than hybrid roles tied to Stockholm.
  • •Onsite or hybrid roles at major banks and payment firms can pay more because they want local ownership and tighter collaboration with compliance and product teams.
• •

  Your stack affects market value.

  • •Engineers who ship production models with Python plus Spark, Kubernetes, feature stores, model monitoring, and cloud infra tend to out-earn notebook-only profiles.
  • •Experience with MLOps in regulated environments is a strong salary driver because it reduces operational risk.
• •

  Company stage changes the comp mix.

  • •Large banks often offer stronger base salary and stability.
  • •Late-stage fintechs may offer lower base but better equity upside; early-stage startups can swing either way depending on funding and runway.

How to Negotiate

• •

  Anchor on business impact, not model elegance.

  • •In fintech interviews and negotiations, talk about fraud saved per month, default reduction, manual review hours removed, or conversion uplift.
  • •Hiring managers care less about “I built XGBoost pipelines” and more about “I reduced chargeback losses by 18%.”
• •

  Separate base salary from total compensation.

  • •Stockholm employers may present pension contributions, bonus plans, and equity as part of the package.
  • •Ask for the exact split: base salary, annual bonus target, pension contribution percentage, sign-on bonus if any, and equity vesting terms.
• •

  Use regulatory complexity as leverage.

  • •If you have experience with GDPR constraints, explainability requirements، model governance، or audit-ready ML pipelines for banking use cases, that is worth money.
  • •Regulated ML is harder to hire for than generic SaaS ML.
• •

  Negotiate against role scope.

  • •If they want you to own experimentation design plus deployment plus monitoring plus stakeholder management, that is not an entry-level or even standard mid-level scope.
  • •Push compensation upward when the job description includes production ownership across the full lifecycle.

Comparable Roles

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  Data Scientist (fintech): typically $72,000 - $118,000 USD

  • •Usually slightly below ML engineer if the role is more analytics-heavy than production-heavy.
• •

  Applied Scientist / Applied Research Engineer: typically $95,000 - $145,,000 USD

  • •Often similar to mid-to-senior ML engineer when the work includes experimentation and model development.
• •

  MLOps Engineer: typically $90,,000 - $140,,000 USD

  • •Strong pay if the role owns deployment pipelines, observability, and model reliability in production.
• •

  Risk Modeler / Quantitative Risk Analyst: typically $85,,000 - $135,,000 USD

  • •Common in banks and lending platforms; compensation rises with statistical depth and regulatory exposure.
• •

  Senior Software Engineer (Payments/Platform): typically $80,,000 - $130,,000 USD

  • •Good benchmark if you are comparing against adjacent engineering roles inside Stockholm fintech.

If you are negotiating in Stockholm as an ML engineer in fintech, the main question is not whether you can “do ML.” It is whether you can ship models that survive production, audits, and real money loss scenarios. That combination commands the best salaries in the market.

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.