Senior Software Engineer I, ML Platform (Brazil)

Dandy is transforming the massive and antiquated dental industry—an industry worth over $400B. Backed by some of the world’s leading venture capital firms, we’re on an ambitious mission to simplify and modernize every function of the dental practice through technology. As we expand our reach globally, Dandy is building the operating system for dental offices around the world—empowering clinicians and their teams with technology, innovation, and world-class support to achieve more for their practices, their people, and their patients. ## What You’ll Do

• Collaborate with Machine Learning Engineers to build the ML training pipelines that process massive 3D datasets, orchestrate model training, and enable continuous model improvements. - Streamline the ML lifecycle, from data labeling and experimentation to deployment, by optimizing internal ML components and reducing technical debt. - Develop and maintain cloud-native systems and tooling (GCP/Kubernetes) that support Dandy’s 3D dental products in a secure, well-tested, and high-performing manner. - Write clean, maintainable code and tests that set the standard for our internal best practices. - Partner with stakeholders across the Engineering organization to influence long-term architectural goals and maintain a high-quality bar. ## What We’re Looking For

• 5+ years of experience working as a Machine Learning Engineer or Software Engineer, ideally within a high-growth startup environment. - Deep proficiency in building and maintaining ML Platform components, such as feature stores, model registries, and distributed training. - Experience with Python-based ML frameworks (PyTorch/TensorFlow) and experience with 3D geometric Computer Vision is a plus. - Deep expertise in large-scale data processing, with proven experience building ML data pipelines to empower complex model training. - Experience creating and maintaining automated build processes across multiple environments (e.g., Buildkite). - Strong background in implementing metrics, logging, and tracing to monitor complex distributed systems. - Ability to communicate concisely about complex architectural problems and propose iterative, pragmatic solutions.