The future of work is increasingly complex — remote workers, distributed teams, flexible multi-tenant office space — and the dynamic of how workers interact with each other and how workers interact with their physical space is changing.
VergeSense is building an easy-to-deploy space utilization & sensing platform that helps real estate professionals monitor foot-traffic within buildings. We are deployed in over 40 million square ft of space, in over 25 Fortune 500 customers, and are paving the path towards $100M in ARR. The core of our occupancy sensing system is ultra-low-power computer vision neural networks which run on the edge, on our in-house built hardware. We are looking for enthusiastic team members who want to work on a truly innovative machine learning platform. The possibilities of our technology are endless, from our core occupancy sensing use-cases, to detecting anything and everything about the physical world, in a privacy-focused way.
This role will:
- Develop, train, and validate CNN models for object detection and object tracking problems with high accuracy.
- Build and develop performant, maintainable, and scalable ML pipeline for model training and evaluation processes.
- Build and maintain high quality datasets for object detection and object tracking models.
- Work with QA to understand the customer pain points and help bring resolution to the issues.
- Write and review technical documents, including requirements and design documents for existing and continuously evolving features of the ML projects.
This role requires:
- BS Computer Science / Electrical Engineering or a related field with 2+ years of experience in systems using machine learning and other artificial intelligence techniques OR MS in Computer Science, Data Science or a related field with 1+ years of experience.
- Working knowledge of more than one programming language (Python, Java, C++ etc.). Proficient in Python is preferred.
- Solid understanding Computer Science fundamentals in data structures, algorithms, and system design.
- Understanding of state-of-the-art Machine Learning techniques, Deep Learning, and Computer Vision.
- Hands-on experience with common machine learning frameworks and libraries – Keras, TensorFlow, Scikit-learn, Pandas, Numpy, OpenCV.
- Experience working closely with data scientists / SWEs and appreciation for their unique workflow.
- Excellent interpersonal, communication and presentation skills, both written and verbal. Ability to collaborate effectively across teams and communicate complex ideas in a simple manner.
- Ability to stay commercially focused and to always push for quantifiable commercial impact.
- Ability to work both independently on ambiguous problems and in highly collaborative team environments.
VergeSense
