ML Ops Engineer

2 weken geleden

Amsterdam, Nederland Harnham Voltijd

MLOps Engineer (Full-Lifecycle) | Early-Stage Startup
Location: Remote or Hybrid (HQ in [City])
Role Type: Full-Time
Start Date: ASAP

#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.

#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.
#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.
Collaborating with ML engineers to transition prototypes into production-ready systems.
Promoting engineering excellence, documentation, and observability.

#3+ years of industry experience in MLOps, ML Engineering, or DevOps for ML systems.
~ Strong experience with cloud platforms (AWS/GCP/Azure) and infrastructure-as-code tools (Terraform, CloudFormation).
~ Strong programming skills in Python and experience with CI/CD tools (GitHub Actions, GitLab CI, etc.).
~ A startup mindset: autonomous, resourceful, and comfortable building systems from scratch.


#A collaborative team culture that values creativity, speed, and experimentation.

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