Applied Research Scientist - Computer Vision

Ambient.ai is a computer vision intelligence company transforming security operations for large enterprises by preventing security incidents before they happen. Ambient.ai has a globally deployed footprint with several F500 companies. The Ambient.ai platform applies AI and computer vision intelligence to existing sensor and camera infrastructure to deliver physical security monitoring and detect threats in real-time. Ambient.ai does this while simultaneously decreasing false alarms by over 95%, allowing security teams to focus on legitimate threats and on rapid response. The future of enterprise physical security is data-driven, intelligent, and proactive.  With Ambient.ai, companies can do more with less, while also improving their security posture.

Founded in 2017 by Shikhar Shrestha and Vikesh Khanna. They are experts in artificial intelligence from Stanford University, who previously built iconic products at Apple, Google, Microsoft, and Dropbox. We are a Series-B company backed by Andreessen Horowitz (a16z), SV Angel, YCombinator, and investment angels like Jyoti Bansal, Mark Leslie, and Elad Gil.

Named on the YC Top Companies List 2021, 2022, 2023 and the Forbes Cloud 100 Rising Stars 2020, we are turning the impossible into the inevitable. We are always looking for passionate people who enjoy solving the toughest problems with cutting-edge AI/ML.

• Implement and train deep neural networks to solve a variety of computer vision problems, such as object detection, semantic scene segmentation, human pose estimation, activity recognition
• Push the state-of-the-art on standard computer vision tasks with massive proprietary video data and state-of-the-art models
• Utilize and improve the infrastructure for training and deploying models, including massive data pipelines, experiment management platforms, visualization tools
• Improve runtime efficiency of models for deployment
• Own data assets and annotation efforts

The amazing skills you'll bring to Ambient.ai:

• BS/MS in Computer Science / Mathematics or related field
• Ideal experience shipping state-of-the-art deep learning models in production or novel research in computer vision
• Experience with deep learning concepts, state-of-the-art in computer vision research, and the mathematics of machine learning
• Strong expertise in deep learning frameworks and architectures, including experience with CNNs, RNNs, Vision Transformers etc..
• Experience with machine learning models, and frameworks such as PyTorch, TensorFlow, etc.
• Proficiency in C/C++ and Python
• Experience with high-quality engineering output (side projects, internships, research projects, full-time jobs)
• The ability and the desire to work in the exciting environment of an early-stage company

Hybrid work environment:

• Employees work from home most days
• The engineering team goes into the San Jose office approximately 4 times per month and as needed for additional team meetings

Why join us:

• We are creating an entirely new category within a 180+ billion-dollar physical security industry and looking for team members who are also passionate about our mission to prevent every security incident possible 
• We have an impressive customer roster of F500 companies, including Adobe, VMware, and SentinelOne
• Regular Full-time employees receive stock options for the opportunity to share ownership in the success of our company 
• Comprehensive health + welfare package (Medical, Dental, Vision, Life, EAP, Legal Services, 401k plan)
• We offer flexible time off to rest and recharge, including Winter Break (time off between Christmas and New Year’s for most roles depending on customer demand)
• The latest tech and awesome swag will be delivered to your door
• Enjoy a full range of opportunities to connect with your awesome co-workers
• We love to hike, are foodies, and love music! Check out our most recent Ambient Spotify Playlist

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We take a market-based approach to pay here at Ambient.ai, and pay may vary depending on multiple factors. The successful candidate’s starting pay will be determined based on job-r