Senior ML Engineer
Job description
A Senior Machine Learning Engineer role at SkinVision, based in the Amsterdam office, responsible for ensuring the Machine Learning team releases models with exceptional performance using state-of-the-art techniques. The role covers the full ML model development lifecycle, MLOps, and mentoring team members.
At a glance
- Work mode
- Hybrid · Amsterdam, Netherlands
What you'll do
- 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, including 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.
What we're looking for
- 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.
Nice to have
- Knowledge of data orchestration tools (Apache Airflow)
- Data modeling (dbt)
- Working in a regulated and/or medical environment
Your team
Machine Learning team
Benefits
- 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
Apply
Direct apply at SkinVision
Opens the job posting at SkinVision
About SkinVision
SkinVision, founded in Amsterdam in 2012, exists to close the gap in access to specialist care for skin cancer. Its proprietary AI is certified as a Class IIa medical device under EU regulation, with over 90% sensitivity and 89% specificity, and has helped over 3 million people worldwide. SkinVision has a database of more than 6 million skin cancer images and can reach 20 million people through insurer partnerships. Where needed, cases are reviewed by a team of dermatologists.
Mission
Making early detection accessible to everyone, everywhere
Key facts
- 2012
- Amsterdam
- Proprietary AI certified as a Class IIa medical device under EU regulation
- Over 90% sensitivity and 89% specificity
- Helped over 3 million people worldwide
- Database of more than 6 million skin cancer images
- Can reach 20 million people through insurer partnerships
- Cases reviewed by a team of dermatologists