Senior Machine Learning Engineer, MLOps

Harnham Netherlands
Relocation
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AI Summary

Lead the development of scalable MLOps infrastructure for real-time fraud detection and payment optimization. Design and maintain CI/CD pipelines, model deployment frameworks, and observability systems. Requires expert Python skills and cloud platform experience to enable data science teams at scale.

Key Highlights
Build and scale production-grade MLOps platform for billions of transactions
Design CI/CD pipelines and real-time inference deployment frameworks
Partner with data science teams to improve model productionization velocity
Key Responsibilities
Design and scale model training pipelines and workflows using modern data platforms
Build and maintain robust CI/CD processes for machine learning systems
Develop model deployment frameworks supporting batch and real-time inference
Improve observability, monitoring, and alerting across ML systems
Contribute to feature store development for both offline and online use cases
Optimize infrastructure for performance, cost, and reliability
Partner with data scientists to productionize models and improve experimentation velocity
Drive best practices in MLOps, platform engineering, and reproducibility
Influence technical direction and support the growth of the ML platform function
Technical Skills Required
Python Cloud platforms (AWS) MLOps and platform engineering
Benefits & Perks
Competitive base salary €91,000 to €107,000
Annual bonus and holiday allowance
Hybrid working model
Relocation support where required

Job Description


Senior Machine Learning Engineer, MLOps Focus

Amsterdam, Netherlands. €91,000 to €107,000 base plus bonus and benefits.


This is an opportunity to take ownership of a modern MLOps platform within a high impact payments environment. The role focuses on building scalable, production grade machine learning infrastructure that directly supports real time decisioning across fraud detection and payment optimisation. You will play a key role in shaping platform standards, improving reliability, and enabling data science teams to deliver models efficiently and safely at scale.


The Company

They are a global technology organisation operating at significant scale, supporting billions of transactions and users worldwide. Their data and machine learning capabilities sit at the core of their product offering, driving performance, security, and customer experience. The organisation is investing heavily in its ML platform, with a focus on standardisation, scalability, and engineering excellence. This role sits within a central platform function that partners closely with data science and product teams.


The Role

You will focus on building and evolving core MLOps capabilities that support the full machine learning lifecycle.

  • Design and scale model training pipelines and workflows using modern data platforms
  • Build and maintain robust CI CD processes for machine learning systems
  • Develop model deployment frameworks supporting batch and real time inference
  • Improve observability, monitoring, and alerting across ML systems
  • Contribute to feature store development for both offline and online use cases
  • Optimise infrastructure for performance, cost, and reliability
  • Partner with data scientists to productionise models and improve experimentation velocity
  • Drive best practices in MLOps, platform engineering, and reproducibility
  • Influence technical direction and support the growth of the ML platform function


Your Skills and Experience

  • Strong commercial experience in MLOps, ML platform engineering, or machine learning engineering
  • Expert level Python for production systems
  • Experience deploying, monitoring, and scaling machine learning models in production
  • Strong understanding of software engineering principles and system design
  • Hands on experience with cloud platforms, ideally AWS
  • Experience with distributed data processing frameworks such as Spark or Databricks
  • Knowledge of model serving and inference systems
  • Experience with infrastructure as code and modern DevOps tooling
  • Strong stakeholder communication skills and experience working with cross functional teams


What They Offer

  • Competitive base salary between €91,000 and €107,000 with flexibility for exceptional candidates
  • Annual bonus and holiday allowance
  • Hybrid working model based in Amsterdam with a collaborative office environment
  • Relocation support where required
  • Opportunity to shape ML platform strategy within a scaling team
  • Exposure to complex, high throughput systems with real world impact
  • Clear progression opportunities as the platform team grows


How to Apply

If you are interested in building scalable ML infrastructure and advancing your career in MLOps, please apply with your CV.


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