Qureos Mentor

Harnham

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 MLOps Engineer
 
 
 
 
 Amsterdam, Netherlands (hybrid working)
 
 
 
 
 Up to 107k annually + benefits
 
 
 
 
 
 
 This is an opportunity to work on large scale, real time machine learning systems that directly impact millions of digital transactions. You will join a growing ML platform team focused on delivering robust, production ready solutions across payments and fraud, with strong ownership and visibility from day one.
 
 
 
 
 
 
 The Company
 
 
 
 They are a global technology organisation operating at the intersection of data, payments, and digital experiences. Their platform supports high volume, real time transactions for well known international businesses, focusing on performance, reliability, and innovation. With a strong engineering culture, they invest heavily in data and machine learning to drive continuous improvement. Teams are collaborative, fast paced, and committed to delivering meaningful impact.
 
 
 
 
 
 
 The Role
 
 
 
 You will focus on building and scaling MLOps capabilities within a production environment, supporting a range of machine learning use cases.
 
 
 
 
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 Design and build scalable systems for training, deploying, and monitoring machine learning models
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 Support real time and batch ML workflows across critical platform services
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 Develop and scale feature store capabilities for both online and offline use cases
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 Improve observability and monitoring across ML systems
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 Collaborate closely with data scientists and engineers to productionise models
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 Take ownership of end to end delivery of ML features and systems
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 Contribute to best practices in MLOps, CI CD, and cloud infrastructure
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 Your Skills and Experience
 
 
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 Strong commercial experience in MLOps or machine learning engineering
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 High proficiency in Python for production level systems
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 Experience deploying and maintaining machine learning models in production environments
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 Knowledge of monitoring, observability, and system reliability
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 Exposure to cloud platforms, ideally AWS
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 Familiarity with ML tools and frameworks such as TensorFlow, PyTorch, Spark, or similar
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 Experience with tools such as Databricks, SageMaker, Kubeflow, or equivalent platforms is beneficial
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 Strong communication skills with the ability to work across technical teams
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 A curious mindset and a practical approach to solving complex problems
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 What They Offer
 
 
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 Competitive salary and benefits package
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 Hybrid working model with a collaborative office environment in Amsterdam
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 Opportunities to work on high impact, large scale ML systems
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 Clear progression and career development within a growing team
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 Supportive engineering culture with strong mentorship and ownership
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 How to Apply
 
 
 
 If you are interested in this Machine Learning Ops Engineer opportunity in Amsterdam, please apply with your CV for immediate consideration.
 
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Senior MLOps Engineer

<div>
 
 
 Senior Machine Learning Engineer, MLOps Focus
 
 
 
 
 Amsterdam, Netherlands. &euro;91,000 to &euro;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.
 
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 Design and scale model training pipelines and workflows using modern data platforms
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 Build and maintain robust CI CD processes for machine learning systems
 </li>
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 Develop model deployment frameworks supporting batch and real time inference
 </li>
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 Improve observability, monitoring, and alerting across ML systems
 </li>
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 Contribute to feature store development for both offline and online use cases
 </li>
 <li>
 Optimise infrastructure for performance, cost, and reliability
 </li>
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 Partner with data scientists to productionise models and improve experimentation velocity
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 Drive best practices in MLOps, platform engineering, and reproducibility
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 Influence technical direction and support the growth of the ML platform function
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 </ul>
 
 
 
 
 
 Your Skills and Experience
 
 
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 <li>
 Strong commercial experience in MLOps, ML platform engineering, or machine learning engineering
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 <li>
 Expert level Python for production systems
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 Experience deploying, monitoring, and scaling machine learning models in production
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 Strong understanding of software engineering principles and system design
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 Hands on experience with cloud platforms, ideally AWS
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 Experience with distributed data processing frameworks such as Spark or Databricks
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 Knowledge of model serving and inference systems
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 Experience with infrastructure as code and modern DevOps tooling
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 Strong stakeholder communication skills and experience working with cross functional teams
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 </ul>
 
 
 
 
 
 What They Offer
 
 
 <ul>
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 Competitive base salary between &euro;91,000 and &euro;107,000 with flexibility for exceptional candidates
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 Annual bonus and holiday allowance
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 Hybrid working model based in Amsterdam with a collaborative office environment
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 Relocation support where required
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 Opportunity to shape ML platform strategy within a scaling team
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 Exposure to complex, high throughput systems with real world impact
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 Clear progression opportunities as the platform team grows
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 </ul>
 
 
 
 
 
 How to Apply
 
 
 
 If you are interested in building scalable ML infrastructure and advancing your career in MLOps, please apply with your CV.
 
</div>

Machine Learning/ML Ops Engineer

Join Harnham and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Harnham

About Company

Senior MLOps Engineer

Machine Learning/ML Ops Engineer