Applied Research Scientist (Computer Vision)
Engineering – Machine Perception
Ambient.ai is a stealth AI company headquartered in Palo Alto on a mission to enable intelligent environments that are safe, efficient and sustainable. Our breakthrough technology combines cutting-edge deep learning with a contextual knowledge model to achieve human-like perception ability. Ambient's flagship product has been deployed by multiple Fortune 100 companies to solve a mission-critical problem in a way that has never been possible.
The company was founded in 2017 by experts in artificial intelligence from Stanford University who previously built iconic products at Apple, Google, Microsoft and Dropbox. We are a Series-A company backed by Andreessen Horowitz (a16z), SV Angel, YCombinator, and visionary angels like Jyoti Bansal, Mark Leslie and Elad Gil.
As a Computer Vision Software Engineer on the Machine Perception team, you will take ownership of Ambient's deep learning infrastructure and computer vision pipelines. You’ll solve challenging research problems and realize novel ideas into products. The ideal candidate for this role would be fluent and up-to-date with Computer Vision research and obsesses about high-quality software engineering to realize research ideas.
- Implementing and training deep neural networks to solve a variety of computer vision problems, such as object detection, semantic scene segmentation, human pose estimation etc.
- Pushing the state of the art on standard computer vision tasks with massive proprietary video data.
- Building and maintaining the infrastructure for training and deploying models, including massive data pipelines, experiment management platform, visualization tools etc.
- Optimizing runtime efficiency of models for deployment.
- Complete ownership of data assets and annotation efforts.
- BS / MS / PhD in Computer Science / Mathematics or related field with 2+ years of deep learning experience (computer vision).
- 3-5 years of software engineering experience in an academic or industrial setting.
- Holistic understanding of deep learning concepts, state of the art in computer vision research and the mathematics of machine learning.
- Experience training a variety of popular deep learning architectures, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) etc.
- Proficiency in at least one of the popular computational and deep learning frameworks, such as TensorFlow, Caffe, Theano etc.
- Proficiency in C/C++ and Python.
- Proven track record of high-quality engineering output (side projects, internships, research projects, full-time jobs etc.).
- The ability and the desire to work in the dynamic environment of an early-stage company.
At Ambient, we respect and admire the builders and the creators. Send us your most incredible project; we'd love to see.