R&D Engineer: AI & Geometry for Digital Orthodontics

Envista Dentistry; Madrid; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Envista is seeking a research engineer/scientist in Computational Geometry, Design Optimization, and Machine Learning to join a cross-functional team including engineers and clinical experts. You will help create next-generation solutions for Spark and Digital Orthodontics, from concept to prototype to handover.

The role emphasizes algorithm development, experiments, and collaboration across disciplines to drive clinical impact and product readiness.

Formación

• Master’s degree in Computer Science, Applied Mathematics, or related field.
• Minimum 3 years of professional R&D experience in Computational Geometry, Design Optimization, Algorithm Design, and Machine Learning.
• Strong mathematics and algorithm design skills; excellent problem-solving abilities.
• Good spoken and written English; strong technical writing skills.

Responsabilidades

• Investigate digital orthodontics workflows to identify automation opportunities.
• Develop advanced algorithms for processing and predicting geometric/meta data.
• Prototype high-fidelity solutions for handover to product teams.
• Design experiments and acceptance criteria to validate technical and clinical relevance.
• Create technical reports documenting findings and proposed solutions.

Conocimientos

Computational Geometry

Design Optimization

Algorithm Design

Machine Learning

Mathematics

English Proficiency

Educación

Master’s degree in Computer Science or Applied Math

PhD (preferred)

Herramientas

C++

OO Design

Design Patterns

3D Modeling Concepts

Descripción del empleo

Envista is seeking a research engineer/scientist in Computational Geometry, Design Optimization, and Machine Learning to join a cross-functional team including engineers and clinical experts. You will help create next-generation solutions for Spark and Digital Orthodontics, from concept to prototype to handover.

The role emphasizes algorithm development, experiments, and collaboration across disciplines to drive clinical impact and product readiness.