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Machine Learning Engineer (ID: 4050)

STAFIDE

Amsterdam
Full-time
5-10 years experience
On-site

Key Skills

Machine Learning
MLOps
Google Cloud Platform
BigQuery
Vertex AI
Terraform
Docker
GitHub Actions
CI/CD
Infrastructure-as-code
Model deployment
Model monitoring
Pricing optimization
Software engineering
Data science

Job Description

As a Machine Learning Engineer – MLOps, you will:
  • Develop, implement, and maintain machine learning models for pricing ancillary products such as seats, bags, extra legroom, and paid fare upgrades.
  • Design, research, and implement end-to-end machine learning pipelines covering model training, retraining, deployment, and monitoring.
  • Lead the MLOps aspects within the team, ensuring robust, scalable, and production-ready machine learning solutions.
  • Design and optimize ML architectures to support reliable and efficient model development and deployment.
  • Continuously monitor, maintain, and improve productionized machine learning models.
  • Ensure low-latency model deployments and adherence to internal engineering standards and best practices.
  • Work extensively within the Google Cloud Platform (GCP) ecosystem for machine learning development and deployment.
  • Leverage BigQuery and the Vertex AI suite for data processing, model development, deployment, and monitoring.
  • Implement infrastructure-as-code using Terraform to provision and manage ML infrastructure.
  • Containerize machine learning applications and services using Docker.
  • Build and maintain CI/CD pipelines using GitHub Actions.
  • Implement testing, automation, and deployment practices to ensure reliable and scalable ML solutions.
  • Collaborate with data science, engineering, and other technical stakeholders throughout the machine learning lifecycle.
What You Bring to the Table:
  • 6–8 years of overall professional experience in Machine Learning, Data Science, or a closely related engineering discipline.
  • Strong hands-on experience developing, implementing, and maintaining machine learning models in production environments.
  • Strong understanding of the complete ML lifecycle, including model development, retraining, deployment, monitoring, and optimization.
  • Strong MLOps experience with ownership of production machine learning workflows and infrastructure.
  • Hands-on experience with Google Cloud Platform (GCP).
  • Experience with BigQuery and the Vertex AI ecosystem.
  • Strong experience with Terraform and infrastructure-as-code practices.
  • Hands-on experience with Docker and containerized ML workloads.
  • Strong experience building and managing CI/CD pipelines using GitHub Actions.
  • Experience with ML architecture design, optimization, testing, and automation.
  • Understanding of production ML monitoring, model performance, reliability, and low-latency deployment requirements.
  • Strong understanding of scalable and maintainable machine learning engineering practices.
You should possess the ability to:
  • Design and implement end-to-end production-grade machine learning pipelines.
  • Develop and maintain ML models that address 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 effective engineering standards.
  • Build and maintain reliable CI/CD pipelines for machine learning 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 machine learning solutions.
  • Implement appropriate testing, monitoring, and deployment practices for production ML systems.
  • Troubleshoot production ML and infrastructure issues and implement sustainable improvements.
  • Collaborate effectively with data scientists, engineers, and other stakeholders.
  • Apply software engineering and MLOps best practices to machine learning development.
What we bring to the table:
  • The opportunity to work on production-grade machine learning and MLOps solutions.
  • Exposure to real-world ML applications involving pricing and optimization of ancillary products.
  • Opportunities to work extensively with GCP, BigQuery, and Vertex AI.
  • Hands-on exposure to modern MLOps technologies including Terraform, Docker, and GitHub Actions.
  • Opportunities to work across the complete machine learning lifecycle, from model development and retraining to deployment, monitoring, and optimization.
  • A collaborative engineering environment focused on scalable, reliable, and high-performance machine learning solutions.
  • Opportunities to contribute to ML architecture, automation, testing, CI/CD, and continuous improvement.
Let’s Connect

Want to discuss this opportunity in more detail? Feel free to reach out.

Recruiter: Aswin Dhanvandhar
Phone: +31 20 369 0609 ; Extn :141

Core Responsibilities

You will design, implement, and maintain end-to-end machine learning pipelines for pricing and product optimization. Additionally, you will lead MLOps practices, ensuring scalable, low-latency model deployments within the Google Cloud Platform ecosystem.

Requirements

Candidates must have 6-8 years of professional experience in machine learning or a related engineering discipline. Strong hands-on expertise in MLOps, GCP, BigQuery, Vertex AI, Terraform, and containerization technologies is required.

About STAFIDE

Industry: Staffing and Recruiting

Company size: 11-50 employees

Headquartered in the Netherlands, STAFIDE specializes in Niche Tech Recruitment across Europe, connecting top talent with outstanding opportunities in the IT sector. Our data-driven recruitment model ensures the ideal match between candidates and employers, enhancing both skill alignment and cultural fit. With a strong focus on Skill-Based Hiring, we provide candidates with an in-depth understanding of the organization—whether for permanent positions or temporary assignments (interim opdrachten) like secondment (detachering)—strengthening employer branding for our clients as a recruitment company (uitzendbureau). In today’s fast-evolving tech landscape, we recognize the unique challenges companies face in sourcing highly skilled talent. Our advanced, AI-driven talent intelligence system (ATS) is specifically designed to prioritize Skill-Based Hiring for niche IT roles, empowering organizations to address talent shortages by identifying professionals with the expertise to drive innovation and growth. Whether you’re a company in search of exceptional talent or a professional seeking your next ICT role, STAFIDE is your strategic recruitment (werving en selectie) partner. Our deep expertise in the Dutch market, combined with a steadfast commitment to excellence, makes us the preferred choice for all your recruitment needs.

Added 2 days ago