Senior MLOps Engineer

Harnham; Amsterdam; Hybrid; EUR 65,000 - 85,000; Full time

Benefits offered by this job

Competitive salary and benefits package

Opportunities for career development

Supportive engineering culture

Job summary

Harnham in Amsterdam is looking for a Machine Learning Ops Engineer to build and scale MLOps capabilities. You will design and implement systems for machine learning model training, deployment, and monitoring while ensuring collaboration with data scientists and engineers.

This role requires strong commercial experience in MLOps, proficiency in Python, and familiarity with a range of ML tools. The company offers a hybrid working model and a supportive engineering culture dedicated to career development.

Qualifications

• Strong commercial experience in MLOps or machine learning engineering.
• High proficiency in Python for production level systems.
• Experience deploying and maintaining machine learning models in production environments.

Responsibilities

• Design and build scalable systems for training, deploying, and monitoring machine learning models.
• Support real time and batch ML workflows across critical platform services.
• Collaborate closely with data scientists and engineers to productionise models.

Skills

MLOps experience

Python proficiency

Production environment maintenance

Monitoring and observability knowledge

Cloud platform exposure

Familiarity with ML tools

Strong communication skills

Curiosity and problem-solving

Tools

AWS

TensorFlow

PyTorch

Spark

Databricks

SageMaker

Kubeflow

Job description

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.

• Design and build scalable systems for training, deploying, and monitoring machine learning models
• Support real time and batch ML workflows across critical platform services
• Develop and scale feature store capabilities for both online and offline use cases
• Improve observability and monitoring across ML systems
• Collaborate closely with data scientists and engineers to productionise models
• Take ownership of end to end delivery of ML features and systems
• Contribute to best practices in MLOps, CI CD, and cloud infrastructure

Your Skills and Experience

• Strong commercial experience in MLOps or machine learning engineering
• High proficiency in Python for production level systems
• Experience deploying and maintaining machine learning models in production environments
• Knowledge of monitoring, observability, and system reliability
• Exposure to cloud platforms, ideally AWS
• Familiarity with ML tools and frameworks such as TensorFlow, PyTorch, Spark, or similar
• Experience with tools such as Databricks, SageMaker, Kubeflow, or equivalent platforms is beneficial
• Strong communication skills with the ability to work across technical teams
• A curious mindset and a practical approach to solving complex problems

What They Offer

• Competitive salary and benefits package
• Hybrid working model with a collaborative office environment in Amsterdam
• Opportunities to work on high impact, large scale ML systems
• Clear progression and career development within a growing team
• Supportive engineering culture with strong mentorship and ownership

How to Apply

If you are interested in this Machine Learning Ops Engineer opportunity in Amsterdam, please apply with your CV for immediate consideration.