Every year, over 34,000 people are severely injured by forklifts in warehouses. We prevent employees from getting injured, while also enhancing the productivity and accuracy of human operators using Computer Vision and Deep Learning. We have tracked and optimized hundreds of thousands of hours of material handling across the US and in Europe, where our camera-based solution has fundamentally changed the way that our customers are running their operations.

We are opening an engineering office in the Bay Area and are looking to bring on additional Software Engineers excited to work at the intersection of cutting-edge Computer Vision and Deep Learning problems. In this role, you will be working with the core engineering team as we maintain and upgrade our perception stack. At first, you will use existing code as a reference to learn how to apply our Software Engineering principles and build internal development tools and libraries. Over time, you will graduate into a role where you will take research prototypes and implement them for production use across our fleet of devices to add additional features and capabilities to our products.

Starting out, you will be primarily focused on the stack that is running on the actual hardware product before expanding to infrastructure provisioning, automated testing, and other internal tools. Depending on interests, there will be an opportunity to shift more toward our AWS backend infrastructure (databases, pipelines, offline analytics infrastructure) as we build out our solution.

As an ideal candidate, you have at least 2-3 years of experience writing Python in a non-academic environment (internships, jobs). You should also have several projects that you completed in Python. Experience with AWS tools (primarily working with Lambda functions, Kinesis streams, and RDS instances) as well as deployment tools like zappa is a big plus. You should know how to work with pip and virtual environments, manage dependencies, how to create documentation for code, write tests with pytest, and work with git, docker, and CI tools.

Most importantly, you have to love writing elegant code efficiently.