Flock Safety provides the first public safety operating system that empowers private communities and law enforcement to work together to eliminate crime. We are committed to protecting human privacy and mitigating bias in policing with the development of best-in-class technology rooted in ethical design, which unites civilians and public servants in pursuit of a safer, more equitable society.
Our Safety-as-a-Service approach includes affordable devices powered by LTE and solar that can be installed anywhere. Our technology detects and captures objective details, decodes evidence in real-time and delivers investigative leads into the hands of those who matter.
While safety is a serious business, we are a supportive team that is optimizing the remote experience to create strong and fun relationships even when we are physically apart. Our flock of hard-working employees thrive in a positive and inclusive environment, where a bias towards action is rewarded. Flock Safety is headquartered in Atlanta and operates nationwide. We have raised $150M in our Series E led by Tiger Global at a $3.5B valuation.
As a Machine Learning Engineer you will research, develop, and support the software that allows our cameras to see like a detective and defines how non-violent crime is eliminated. The ideal candidate is someone who is passionate about taking cutting edge research and technology to solve new problems, and enjoys working with the entire lifecycle of Machine Learning software.
Main Stack: Typescript (Node.js), React, Golang, Postgres, Elastic, Dynamo. Hosted on AWS (k8s, sns) using Docker.
Camera Firmware: Embedded Android running on a custom PCB that we develop in house.
Machine Learning: Pytorch, TensorFlow, TF Serving, Computer Vision, Kubernetes