Senior ML Engineer - Healthcare AI (Amsterdam, Hybrid)

DeepCamp; Amsterdam; Hybrid; EUR 85,000 - 120,000; Full time

Benefits offered by this job

Hybrid working policy

Salary and benefits package

Team events and off-sites

Unlimited skin checks for you

Job summary

SkinVision is seeking a Senior ML Engineer based in Amsterdam to own and drive the full ML lifecycle for our medical AI models. You will design, train, and deploy models with state-of-the-art techniques, mentor teammates, and align ML work with medical device standards.

Experience deploying in production and collaborating with stakeholders is essential. The role emphasizes developing robust ML pipelines in the cloud, working in a regulated environment, and contributing to the ML roadmap within a

Qualifications

• 8-10 years of proven professional experience as a Machine Learning Engineer or similar role.
• Experience deploying ML models to production in a consumer product, preferably in a regulated environment.
• Hands-on experience with MLOps for scalable training, deployment and monitoring.
• Strong ability to translate user needs and requirements into technical plans.
• Excellent communication and presentation skills, with ability to explain technical concepts to diverse audiences.

Responsibilities

• Drive the full ML model development lifecycle from problem definition to deployment and monitoring.
• Create data collection requirements for both new and existing models.
• Develop and improve ML training pipelines in the cloud (AWS or similar).
• Involve stakeholders throughout development and deployment lifecycle.

Skills

Model training

MLOps

Data analysis

Stakeholder management

Team mentoring

Deep learning architectures

Python

Communication skills

Education

Bachelor's or Master's in Data Science/Computer Science/related field

Tools

Apache Airflow

dbt

AWS

Python

Job description

SkinVision is seeking a Senior ML Engineer based in Amsterdam to own and drive the full ML lifecycle for our medical AI models. You will design, train, and deploy models with state-of-the-art techniques, mentor teammates, and align ML work with medical device standards.

Experience deploying in production and collaborating with stakeholders is essential. The role emphasizes developing robust ML pipelines in the cloud, working in a regulated environment, and contributing to the ML roadmap within a