Deep Learning Engineer, Multimodal Vision Platform

Job description

About Matroid 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. What you’ll do 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 What you bring to the table 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 Bonus points if... 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 What we offer in return Competitive pay and equity The chance to constantly work on stimulating intellectual challenges Gym membership reimbursement Free lunch, healthy drinks, and snacks every day Medical, dental, and vision insurance with 100% paid premiums Flexible hours, with room for the occasional day away when life calls for it A budget for whatever hardware or software will make you most effective Regular tech talks on the latest advances in CV, DL, and engineering