Deep Learning Engineer, Multimodal Vision Platform

Matroid is a full-service computer vision company that has developed an end-to-end platform allowing enterprise customers to rapidly train and deploy automated visual inspection on imagery including EO, IR, X-Ray, CT, OCT, and others. Founded in 2016 by a Stanford professor, Matroid has a broad and rapidly growing set of customers in manufacturing, industrial IoT, government and security.

We are looking for a Deep Learning Engineer to build the models, capabilities, and systems at the heart of our multimodal vision platform. This is a broad and deeply technical role, with significant ownership and impact. You’ll rapidly take ideas from research all the way to production: apply the latest techniques to build and deploy new platform capabilities, solving visual inspection for our customers. You’ll work in a fast-paced environment alongside experts who are passionate about their work.

This position is onsite five days a week at our downtown Palo Alto office, near the Stanford campus and Caltrain.

• →Research: Critically analyze the latest research in computer vision and deep learning, and decide what’s worth adapting for use in our platform
• →Build: Design, adapt, and train models across detection, segmentation, anomaly detection, tracking, video understanding, vision-language, and 3D reconstruction tasks
• →Engineer: Turn new models and techniques into platform capabilities that customers can train and deploy on their own data and use cases
• →Deploy: Optimize architectures & deployment systems for fast, cost-efficient inference, from cloud GPUs to small edge devices
• →Collaborate: Work with product, infrastructure and field engineering teams to drive your models & capabilities from idea to customer impact

• Master’s in Computer Science, Software Engineering, Mathematics, or a related field, or a Bachelor’s with equivalent experience
• Excitement about the full range of this work, whether it's building novel video transformer architectures, getting realtime segmentation running on a tiny edge device, or making 3D reconstruction work reliably on customer data
• 3+ years of industry and/or academic experience in deep learning, computer vision, and software engineering
• Experience building ML systems & capabilities, not just scripts & one-off experiments
• Familiarity with modern architectures and techniques: the latest foundation models, how they work, what you can do with them
• Strong software engineering skills in Python and PyTorch; you care about the quality of your code
• Solid oral, written, presentation, collaboration, and interpersonal communication skills

• Significant computer vision and deep learning research experience
• Prior work applying computer vision to real-world use cases
• Experience productionizing models, including inference optimization (e.g. TensorRT, ONNX) and serving (e.g. Triton Inference Server)
• Experience with 3D reconstruction and scene representation (e.g. COLMAP, VGGT, 3D Gaussian splatting, world models)
• Experience building or operating multi-tenant ML products
• Open-source contributions to ML tooling, cool personal projects, competitions, or hackathons
• Previous work at high-growth technology startups