About this role
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. You’ll rapidly take ideas from the latest research all the way to production: apply the latest techniques to build and deploy new platform vision capabilities used by 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 & Models
- Critically analyze the latest research in computer vision and deep learning, and decide what’s worth adapting for use in our platform
- Design, adapt, and train models across detection, segmentation, anomaly detection, tracking, video understanding, vision-language, and 3D reconstruction tasks
Platform
- Turn new models and techniques into platform capabilities that customers can train and deploy on their own data and use cases
- Build training systems and capabilities that are adaptive and reliable on datasets we’ve never seen
Production
- Optimize architectures & deployment systems for fast, cost-efficient inference, from cloud GPUs to small edge devices
- Work with product, infrastructure and field engineering teams to drive your models & capabilities from idea to customer impact
How you’ll be doing it
- Operating in a collaborative but highly autonomous environment where you are empowered to make an impact
- Knowing that everything you build affects real-world users, with corresponding quality standards for your work
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
- Familiar 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