Deep Learning Engineer, Multimodal Vision Platform

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