Machine Learning Engineer

Our Company

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. Data from our platform is used to improve building layout & design, execute dynamic workforce strategies, and reduce energy costs. For large clients, the financial impact is in the tens of millions per year. We provide a full-stack solution comprised of easy-to-deploy AI-sensors, fleet management tools, analytics software, and APIs that integrate with the leading workplace management systems on the market.

Current Events

We are in unprecedented times, and workplace tech is especially needed to help companies plan for a post-COVID workplace. Our AI-powered sensing products and platform are being called on more than ever to serve commercial real estate operators and employees of the modern workforce. We have been at the center of space planning conversations focused on helping companies comply with public health guidelines of social distancing, sanitation, among other applications. As companies plan the return to work for their teams, we are working with speed, accuracy, and care to deliver a crucial service in this transitional time.

Our Product

Deployed in minutes, our high-accuracy quick-installation sensors are able to identify the presence of people and key objects in the context of an office environment that signal how space is being used. Our analytics platform creates a sphere of intelligence within properties and provides actionable insights and AI-powered recommendations to help building managers make effective space planning decisions.

We’re building and training our sensors to become even smarter, with the goal of catering to an even wider range of customers, use cases, and industries. Our sensor-as-a-system and intuitive analytics dashboard provide a real-time view into what is happening in a space, and over time our sensors automatically learn to detect new types of events on the go.

Our Community

We are a lean, fast-moving, impact-focused (and fun!) team of 60+ across San Francisco HQ, Minneapolis, Boston, and remote locations. We count the Fortune 500 among our customers and are backed by leading investors including Y Combinator, Allegion Ventures, JLL, Bolt, Pathbreaker Ventures, with strong financial runway. We're always looking to add amazing individuals to our team.

We believe in allowing people to apply their strengths toward doing work they find meaningful. We value creativity and resourcefulness in team members, and would love to hear where you believe your contributions would be most impactful.

Skills: C++, Python, TensorFlow, Computer Vision, Internet of Things (IoT)

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.

On the software-side, our current stack uses Rails, React, Heroku, a variety of AWS Services (AWS IoT, Redshift, DynamoDB), Docker (for managing fleets of IoT devices) and Tensorflow for machine-learning.

For the hardware-side piece of our product, we're using ESP MCUs, gateway devices that run Ubuntu Core, Raspberry Pis (for prototyping), and a variety of different sensors (image, PIR, temperature / environmental, etc).