ML Ops Engineer

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Amsterdam / €60000 - €65000 annum

INFO

Salary
SALARY:

€60000 - €65000

Location

LOCATION

Amsterdam

Job Type
JOB TYPE

Permanent

Job Opportunity: MLOps Engineer (Full-Lifecycle) | Early-Stage Startup

Location: Remote or Hybrid (HQ in [City])

Role Type: Full-Time

Start Date: ASAP

About the Company

The company is a small, fast-moving startup building [short description of product/mission]. With a lean, collaborative team focused on delivering real value through AI, they are seeking an experienced MLOps Engineer to own and optimize their end-to-end machine learning pipeline as they scale.

The Role

As the company's first dedicated MLOps hire, the successful candidate will be responsible for establishing and maintaining the full MLOps lifecycle-from data ingestion and experimentation to deployment, monitoring, and continuous optimization. They will work closely with ML engineers and the product team to ensure models move into production smoothly, reliably, and efficiently.

Responsibilities

  • Designing, building, and maintaining scalable ML pipelines (training, validation, deployment).
  • Developing CI/CD workflows for ML models and data pipelines.
  • Implementing model and data versioning, lineage tracking, and reproducibility best practices.
  • Managing infrastructure for training and inference (cloud, containers, orchestration).
  • Building monitoring systems for data drift, model performance, and operational reliability.
  • Optimizing cost, performance, and automation across the ML lifecycle.
  • Collaborating with ML engineers to transition prototypes into production-ready systems.
  • Promoting engineering excellence, documentation, and observability.

Qualifications

  • 3+ years of industry experience in MLOps, ML Engineering, or DevOps for ML systems.
  • Proven experience managing the full ML lifecycle in production environments.
  • Strong experience with cloud platforms (AWS/GCP/Azure) and infrastructure-as-code tools (Terraform, CloudFormation).
  • Hands-on expertise with containerization and orchestration (Docker, Kubernetes).
  • Familiarity with ML pipeline tools (Kubeflow, Airflow, MLflow, Vertex AI, SageMaker, etc.).
  • Strong programming skills in Python and experience with CI/CD tools (GitHub Actions, GitLab CI, etc.).
  • Understanding of monitoring, tracing, alerting, and model observability tools.
  • A startup mindset: autonomous, resourceful, and comfortable building systems from scratch.

What the Company Offers

  • High ownership and the opportunity to shape the ML infrastructure from the ground up.
  • A collaborative team culture that values creativity, speed, and experimentation.
  • Competitive salary + equity package.
  • Flexible work environment.
  • A chance to have significant impact on a product used by real customers.

CONTACT

Charlotte York

Managing Consultant ? Netherlands

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