Sr. Machine Learning Engineer - 3D Modeling

Role overview Build and operate machine learning systems and AI features, taking them from experimentation into production. A major focus is creating image-to-3D workflows that produce printable models, alongside broader ML pipelines and practical LLM applications. The position is listed as hybrid in Montevideo or remote within Latin America.

Responsibilities - Develop, deploy, and maintain machine learning models and AI features used in production systems. - Create image-to-3D pipelines, including model generation, mesh repair, segmentation, and preparation for slicers. - Own end-to-end ML pipelines covering data ingestion, feature engineering, training, evaluation, and serving. - Build LLM applications using techniques such as prompt design, retrieval-augmented generation, observability, and orchestration frameworks. - Integrate ML systems with backend and data engineering infrastructure. - Monitor production models and contribute to experiment tracking, model versioning, CI/CD, and observability practices.

Requirements - At least three years of professional machine learning or AI engineering experience. - Strong grounding in supervised and unsupervised learning, feature engineering, and model evaluation. - Experience shipping ML systems to production. - Proficiency in Python and a deep learning framework; PyTorch is preferred. - Experience building and using APIs with a framework such as FastAPI, Flask, or Django. - Practical LLM experience, plus familiarity with cloud ML tooling, Docker, testing, version control, and CI/CD. - Advanced spoken and written English for working with English-speaking stakeholders.

Nice to have - Experience with 3D geometry, meshes, point clouds, image-to-3D workflows, mesh repair, slicers, or CAD tools. - Computer vision and generative model experience, including GPU-based inference and assessing output quality. - Familiarity with model evaluation and responsible AI practices, and interest in current ML research.

Benefits and work setup - Hybrid work in Montevideo or remote work from Latin America.