MLOps Engineer — Pricing ML on GCP & Vertex AI

Stafide; Amsterdam; On-site; EUR 90,000 - 140,000; Full time

Job summary

Stafide is seeking a Machine Learning Engineer – MLOps to design, implement, and maintain end-to-end ML pipelines in production. You will own MLOps practices, working with GCP, Vertex AI, and BigQuery to deliver scalable, low-latency ML solutions for pricing ancillary products.

You will lead the full ML lifecycle from development and retraining to deployment and monitoring, collaborating with data scientists and engineers to ensure robust, automated CI/CD pipelines using GitHub Actions and

Qualifications

• 6–8 years of professional experience in ML, Data Science, or related engineering.
• Strong hands-on experience developing, implementing, and maintaining ML models in production.
• Strong understanding of the ML lifecycle from development to deployment and optimization.
• Hands-on MLOps experience with ownership of production ML workflows and infrastructure.
• Experience with Google Cloud Platform (GCP).
• Experience with BigQuery and Vertex AI ecosystem.
• Strong Terraform and infrastructure-as-code practices.
• Hands-on Docker experience with containerized ML workloads.
• Experience building and managing CI/CD pipelines (GitHub Actions).
• Experience in ML architecture design, optimization, testing, and automation.
• Understanding production ML monitoring, performance, reliability, and low-latency requirements.
• Strong knowledge of scalable, maintainable ML engineering practices.

Responsibilities

• Design and implement end-to-end production-grade ML pipelines.
• Develop and maintain ML models addressing real-world pricing and product optimization problems.
• Manage the complete model lifecycle from development and retraining through deployment, monitoring, and continuous improvement.
• Design scalable ML architectures and optimize them for performance, reliability, and low-latency execution.
• Lead MLOps practices within a technical team and establish engineering standards.
• Build and maintain CI/CD pipelines for ML applications.
• Automate infrastructure provisioning and management using Terraform.
• Containerize and deploy ML workloads using Docker.
• Work effectively with GCP, BigQuery, and Vertex AI for production ML solutions.
• Implement testing, monitoring, and deployment practices for production ML systems.
• Troubleshoot production ML and infrastructure issues and implement improvements.
• Collaborate with data scientists, engineers, and stakeholders.
• Apply software engineering and MLOps best practices to ML development.

Skills

ML lifecycle mastery

MLOps ownership

GCP experience

BigQuery

Vertex AI

Terraform

Docker

GitHub Actions

CI/CD pipelines

Production ML monitoring

Tools

GCP

BigQuery

Vertex AI

Job description

Stafide is seeking a Machine Learning Engineer – MLOps to design, implement, and maintain end-to-end ML pipelines in production. You will own MLOps practices, working with GCP, Vertex AI, and BigQuery to deliver scalable, low-latency ML solutions for pricing ancillary products.

You will lead the full ML lifecycle from development and retraining to deployment and monitoring, collaborating with data scientists and engineers to ensure robust, automated CI/CD pipelines using GitHub Actions and