Senior MLOps Engineer — Real-Time ML at Scale

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

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.