Focus: Deep Learning and Computer Vision
Location: Seattle, Washington
XNOR.ai brings state-of-the-art artificial intelligence to the edge. XNOR’s platform allows companies to run complex deep learning algorithms, formerly restricted to the cloud, locally on a range of devices including mobile phones, drones, and wearables. This new, highly scalable approach ensures complete privacy of data, eliminates the need for connectivity, and significantly reduces memory load and power demands, all without compromising accuracy or performance. XNOR is a venture-funded startup, founded on award-winning research conducted at the University of Washington and the Allen Institute for Artificial Intelligence. XNOR’s industry-leading technology is used by global corporations in aerospace, automotive, retail, photography, and consumer electronics.
As a team, we are working to define and solve the hardest problems in computer vision and AI. Our roots are in research, which means at our core we value learning, intellectual curiosity, and self-starters. When we founded XNOR, we were bold enough to say we can build a better solution for edge devices than relying on cloud computing. As the company scales, we are actively solving some of the world’s largest global corporations’ most important problems that can only be tackled by bringing intelligence to devices. This means our work needs to be, not only innovative and precise, but also fast, highly reliable, and seamless across a variety of platforms.
As a machine learning engineer on the XNOR team, you will have the unique opportunity to be part of a fast-paced startup team operating out of the world-renowned Allen Institute for Artificial Intelligence (AI2) with close ties to the research community at the University of Washington. As part of the first company to pioneer deep learning on CPUs, you will have an active role in shaping how different forms of artificial intelligence operate on a range of devices. Unlike being in a big company where you will likely be working on established models and systems, at XNOR, your work will be new and of the highest impact — disrupting cloud computing to shape the future of AI at the edge!
- Proficient in Python
- Experience in working with at least one deep learning framework, for example, PyTorch, Torch, TensorFlow, Caffe
- Working knowledge of C/C++
- Machine learning courses or equivalent practical machine learning experience
- Train new models
- Optimize models
- Collaborate on new learning frameworks
- Deliver models to core engineering team to be deployed on a range of embedded devices
- Competitive salaries and stock options
- Comprehensive health care plan
- Support for obtaining a visa through its immigration attorney, and pays the necessary expenses
- Vacation policy/paid time off
- Conference travel
- Culture of learning
- Healthy lunch and snacks
- Regular team activities
- Standing Desks
- Waterfront views
XNOR.ai is proud to be an Equal Opportunity employer.