ML engineer

Skin cancer is highly treatable when caught early, but limited access to specialist care and long wait times delay diagnosis, increasing the risk of late-stage cases and driving up treatment costs. SkinVision, founded in Amsterdam in 2012, exists to close that gap. Our proprietary AI — certified as a Class IIa medical device under EU regulation, with over 90% sensitivity and 89% specificity — has already helped over 3 million people worldwide.

• Drive the full ML model development lifecycle: from understanding and co-defining the problem to providing inputs on data collection, assessing the quality of data, model training, validation, deployment and monitoring.
• Create requirements for data collection for both new and existing models. This includes data for model training and testing.
• Develop and improve efficient ML training pipelines in the cloud (AWS or similar).
• Involve stakeholders appropriately during the entire development, deployment and monitoring lifecycle.
• Scale the ML environment and processes to multiple models being developed and deployed simultaneously.
• Ensure ML development aligns with medical device standards if applicable, including ML best practices, experiment tracking, traceability, data lineage and documentation.
• Support and mentor team members.
• Showcase ML models and capabilities both internally and externally, by giving presentations, workshops, training, etc.
• Stay abreast of the latest industry standards, best practices and emerging trends in Machine Learning and AI and share insights with the broader team.

• For this role, we will only consider candidates who are currently based in the Netherlands.
• 8-10 years of proven professional experience as a Machine Learning Engineer or similar role, showcasing exceptional proficiency in model training, deployment within a consumer product, data analysis, stakeholder management and teamwork/mentoring.
• Bachelor's or Master's degree in Data Science, Econometrics, Statistics, Computer Science or a related field.
• Ability to translate user needs and requirements into technical requirements and a development plan.
• Hands-on expertise with modern deep learning architectures and other ML architectures, ideally but not restricted to image data.
• Hands-on experience with MLOps practices for scalable training, deployment and monitoring.
• Experience in developing and deploying ML models for a consumer product (mature development processes), ideally in the healthcare space or a regulated environment.
• Ability to iterate quickly from ideas to experiments, learning from results and making data-driven decisions.
• Strong analytical mindset, problem-solving skills and the ability to extract actionable insights from intricate datasets.
• Excellent communication and presentation skills, with the capacity to effectively convey technical concepts to diverse audiences.
• Proven ability to thrive in a collaborative, cross-functional team environment, managing multiple priorities and deadlines.
• Experience with mentoring and leading team members.
• Будет плюсом: Knowledge of data orchestration tools (Apache Airflow), data modeling (dbt) and working in a regulated and/or medical environment are a plus!

• A competitive salary, additional benefits, and a hybrid working policy
• A vibrant, dynamic, and rapidly growing scale-up in Amsterdam
• An enthusiastic, professional, and international team
• Regular team events, including off-sites and fun activities
• Unlimited skin checks for you