Senior ML Engineer — Medical AI, Amsterdam (Hybrid)

SkinVision BV; Amsterdam; Hybride; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Hybrid work policy

Amsterdam office

Unlimited skin checks

Résumé du poste

SkinVision BV in Amsterdam is seeking a Senior Machine Learning Engineer to lead model development and deployment for a consumer product. You will own end-to-end ML pipelines in AWS, mentor teammates, and align ML work with medical device standards.

The role emphasizes collaboration across product, engineering, and regulatory teams, with hands-on experience in training, deploying, and scaling vision models and performing MLOps.

Qualifications

• 8-10 years of professional experience as a Machine Learning Engineer or similar role.
• Bachelor's or Master's degree in Data Science, Econometrics, Statistics, Computer Science or related field.

Responsabilités

• Drive the full ML model development lifecycle from problem framing to deployment and monitoring.
• Create data collection requirements for new and existing models.
• Develop and improve ML training pipelines in the cloud (AWS).
• Involve stakeholders throughout the development and deployment lifecycle.
• Scale ML environments for multiple models deployed simultaneously.
• Ensure ML development aligns with medical device standards where applicable.
• Mentor team members and contribute to the ML roadmap.
• Present ML capabilities internally and externally to showcase impact.
• Keep up-to-date with industry standards and best practices.

Connaissances

Model training and deployment

MLOps

Deep learning architectures

Data analysis

Stakeholder management

Mentoring

Communication

Formation

Data Science/Bachelor's or Master's

Outils

Apache Airflow

dbt

AWS

Description du poste

SkinVision BV in Amsterdam is seeking a Senior Machine Learning Engineer to lead model development and deployment for a consumer product. You will own end-to-end ML pipelines in AWS, mentor teammates, and align ML work with medical device standards.

The role emphasizes collaboration across product, engineering, and regulatory teams, with hands-on experience in training, deploying, and scaling vision models and performing MLOps.