Transparency and accountability through machine learning
Today, officers spend 65% of their time dealing with paperwork, leaving only 35% of their time available to build deep relationships with the communities that they serve. Axon's mission is to improve transparency, accountability, and productivity in law enforcement via technology.
Axon Research's goal is to use deep learning to accelerate the many manual human workflows in public safety data, so that officers can spend more time with what matters most: the community. We focus on workflows, while continuing to entrust decision-making to officers.
Our product is a machine learning platform that uses deep learning to understand video footage and power three key use cases:
Accelerated footage review to enable supervisors to better understand their officers' behavior and provide positive or negative feedback in order to improve training and police/community relations.
Automated redaction to speed up the process of sharing footage with the public while protecting the privacy of citizens captured in video.
Automated reporting to populate factual records directly from video and audio, so officers can spend more time serving the community.
By removing the burden of manual notes and endless hours of keyboard work, officers can be present, build relationships and be more human. We want our technology to enable more personal interactions to help build safer and stronger communities.
How we do it
Axon Research is a group comprised of machine learning researchers and developers. We balance an aggressive roadmap of engineering challenges with a portfolio of research bets. All of our engineering work is in service of ML, and all of our research work will make major impacts to product if successful. We understand the importance of collaboration for rigorous research and our whole team is encouraged to publish and open-source. As the deep learning technology and team came from the acquisition of Dextro, we maintain a highly startup-centric culture.
Like Apple, Axon is a vertically-integrated company that builds the entire stack, from camera hardware to firmware to cloud evidence management solutions, and now all the way up to AI. This tight coupling enables incredible scale with machine learning across both training and inference.
Our work requires much more care than typical AI applications such as targeting ads or tagging photos; therefore, we are investing time into a whole new level of applied AI security, including understanding adversarial examples, as well as a wholly independent AI ethics board that guarantees that our work will be used only for transparency and accountability, never for surveillance.
We're building a team that spans diversity of all kinds, which we think is critical in our mission to bring officers and the communities they serve closer together. If this is something you care about, we would love to have you join us.
Our machine learning systems depend on training data to continue to improve and learn new things over time. In this role, you will develop our data annotation system, a user-facing experience that gives an easy way for our customers and internal annotators to teach our ML models what things like “officer leaving car” looks like. Essentially, you'll own the system that turns a bunch of video footage into a graph of concepts and relationships that the ML models can understand.
When we say full-stack, we mean full-stack--we're a really lightweight team and you'll have a ton of responsibility.
Who you are:
- You already have experience with building large, high-scale web applications (well-designed APIs, high volume data pipelines)
- You naturally gravitate to A/B testing to optimize the experience on our platform.
- You're excited about machine learning and are interested in working with scientists and ML engineers to further your knowledge.
- Bonus plan
- Stock options
- Supportive parental leave policy
- Unlimited paid-time-off
- Stocked kitchen
- Opportunities to ride along with real US police officers in real life situations, see them use technology, and get inspired.
- And much more...