Senior Computer Vision Engineer

Labelbox’s mission is to build the best products for humans to advance artificial intelligence. Real breakthroughs in AI are reliant on the quality of the training data. Our training data platform enables organizations to improve their machine learning models far quicker and more accurately. We are determined to build software that is more open, easier-to-use, and singularly focused on getting our customers to performant ML faster.  
Current Labelbox customers are transforming industries within insurance, retail, manufacturing/robotics, healthcare, and beyond. Our platform is used by Fortune 500 enterprises including Allstate, Black + Decker, Bayer, Warner Brothers and leading AI-focused companies including FLIR Systems and Caption Health. We are backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures (Google's AI-focused fund), Databricks Ventures, Snowpoint Ventures and Kleiner Perkins.
About the Perception Team The vast majority of machine learning projects fail because of insufficient or poorly labelled data. At Labelbox, the Perception team’s mission is to build the most efficient tool for creating high-quality training data, allowing our users to make breakthroughs in their domains and advance the field of artificial intelligence. Our team focuses on building a beautiful browser interface, that is served to users all around the world. We focus on use cases that allow humans to annotate media around languages such as audio waveforms, text documents, and PDFs.
About the Role
As our Senior Computer Vision Engineer you will be considered as the subject matter expert for computer vision in engineering and will be deploying state-of-the-art computer vision models that run live in the Labelbox video editor. You will also be researching, proposing and implementing computer vision approaches to make our image and video editors best-in-class.

About You

• You have 4+ years of experience as a Computer Vision (CV) engineer
• You have experience adapting deep learning methods with traditional computer vision methods to build robust, configurable systems
• You have experience training and deploying machine learning models for object detection, classification, tracking, and segmentation, using frameworks such as PyTorch and Tensorflow
• You are able to effectively work with 2D and 3D datasets from various sensors to develop generative and discriminative models
• You feel comfortable implementing image processing, graphics (3D and 2D), and computer vision libraries (OpenCV, OpenGL, etc) to manipulate training data, automate labeling and update algorithms
• You have an eye for connecting the deep learning algorithms to the humans that interface with the Labelbox platform via the testing and development of different AI design techniques to optimize throughput and detection rates
• Quality and testing are essential to you but can balance between perfection and shipping
• You are able to bring trained models into production by deploying/integrating them into resource constrained environments, using techniques such as optimization

Do great work. From anywhere.
We hire great people regardless of where they live. Work wherever you’d like as reliable internet access is our only requirement. We communicate asynchronously, work autonomously, and take ownership of our work.
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