Machine Learning Engineer - Multimodal

Job description

Job responsibilities

• Research, develop, and deploy multimodal models that understand content from manufacturing documentation end-to-end, replacing traditional OCR-to-NLP cascades with unified architectures
• Work alongside the core-engineering team to build and maintain annotation tooling, implement active learning loops, and engineer synthetic data augmentation strategies
• Develop evaluation frameworks that quantify system behavior and user impact, extending beyond traditional benchmark metrics
• Collaborate with the other members of the machine learning team to set the technical and product roadmaps for the AI platform
• Burn down the long tail, as every percentage point of accuracy maps to man-years of time savings at our scale

Job requirements

• 5-8 years of professional deep learning experience, with at least 2 years working on multimodal models leveraging image and text modalities
• Strong Python and PyTorch fluency: You've written custom training loops, loss functions, and data loaders from scratch when needed
• Production deployment ownership: You've shipped models to production and have been responsible for endpoint and model health
• MS or PhD in Computer Science, Electrical Engineering, or related field preferred; equivalent industry experience valued equally