About curbFlow
curbFlow uses computer vision technology to convert the digital cameras of businesses & organizations into data collection machines. There are over a Billion IP cameras in the world, and curbFlow’s mission is to make them much more valuable to their commercial owners. Clients connect their video to curbFlow to get real-time, business-critical data like pedestrian counts for retail, guest tracing for commercial real estate, traffic counts for DOTs and engineering firms, employee engagement at restaurants, and live wait times for amusement park rides, to name a few of our use cases.
Paying clients include Taco Bell/Yum Brands, NYC’s largest 7-11 franchisee, Goodwill, Brightline, Merlin Entertainments (owner of Legoland) and JBG Smith, developer of Amazon’s HQ2.
curbFlow was seed-funded with $8mm in 2018 by venture capital firms General Catalyst and Initialized Capital (Garry Tan) and expects to raise a Series A by the end of 2022.
Leadership & Culture
curbFlow is founded and led by three former Y Combinator founders with two exits under their belts. The company has operated as a distributed team since its founding in 2018. Team members currently live in DC, NY, Texas, the Bay Area and Canada.
The Role
We’re searching for talented lead computer vision engineers with a track record of demonstrated high achievement who can take responsibility for the full software development lifecycle, including a) conducting research on the state of the art; b) implementing software modules for our perception stack; c) integrating new tools into our embedded and cloud platforms.
This team member will be responsible for the design and development of all aspects of our perception stack, including object detection, classification, tracking, and localisation. The ideal candidate will use a mixture of traditional and DL based computer vision techniques and will have deep expertise in at least one of the technical areas mentioned above.
This will be a very hands-on role, delivering customer facing solutions for real business.
About You and How you Succeed at curbFlow
You’re excited about building a product that hasn’t been built before. You have a bias toward action when you are stuck but are not afraid to ask for help when you need to. You’re eager to test new ways of doing things and can take advantage of the freedom an early stage startup can afford you. You are eager to engage not only with the business side of the team, but with the clients and users themselves.
Responsibilities:
- Design and build computer vision solutions in the areas of object detection and tracking, scene segmentation, scene understanding, and depth estimation
- Optimize algorithms to run in real-time on edge and on the cloud
- Build solutions that are robust to camera motion, occlusions, poorly exposed scenes
- Create critical infrastructure and best practices as we scale our computer vision team
- Work with a growing team of software and machine learning engineers
- Maintain data pipelines critical to testing and training our algorithms
- Define labeling ontologies and create training, validation, and testing sets across customer sites and weather conditions
- Develop algorithms, perception software modules and libraries with responsibility for the full software engineering lifecycle: requirements, design, source code implementation, integration, and system test
Qualifications:
- Masters degree in computer science or relevant field with exposure to classic and modern computer vision and machine learning techniques (PhD preferred)
- 3+ years of professional Python experience/expertise training, evaluating, and deploying models with one of more common deep learning framework such as PyTorch or Tensorflow, Keras, Lightning, etc
- Sufficient familiarity with traditional computer vision and machine learning techniques (e.g., pca)
- Deep insight and experience on modern computer vision and machine learning techniques (e.g., cnn based object detection, multi-object tracking)
- Familiar with popular computer vision solution related frameworks, such as opencv, gstreamer, ffmpeg, deepstream, tensorrt, etc..
- Experience with Linux environment and targeting embedded deployment
- Experience with public cloud such as GCP, Azure or AWS
- Excellent written and verbal communication skills
- Ability to design, implement, present, and operate independently without oversight
- Good business insight and exceptional analytical skills
Nice to Haves:
- Experience working with embedded systems like Nvidia Jetson, Raspberry PI, etc.
- Hands on experience with backend engineering development
- Experience with SaaS business
- Excellent project management skills
What we offer
- Opportunity to shape an early-stage, mission-driven startup
- Live anywhere you want in North America - Speed matters to Scale, so we are building a distributed team of the best talent fast
- Professional growth at a fast-growing, venture-funded start-up with a proven founder
- Competitive salary and meaningful equity for early team members
- Unlimited vacation days
- Generous health benefits (Health, Vision, Dental)
- 401k
- Brand new, top of the line hardware and whatever else you need to help you win
Why bet on Computer Vision and curbFlow?
1. Huge industry hiding in plain sight: auto-measuring physical activity at scale
2. Large chasm between customer knowledge and market availability, i.e. customers don’t know what is available in the market
3. No clear leader; everyone is small and unbranded (i.e. no Amazon or Google in the room to compete with)
4. The tech is very modular, allowing curbFlow and its customers to invent whole new use cases on a regular basis
5. curbFlow has developed the tech and data pipelines over three years and invested several million dollars and is now ready to scale
6. curbFlow is already emerging as the market leader in auto-measuring with CV by working with customers like Merlin Entertainment, Taco Bell/Yum!, Goodwill, JBG Smith, City of Washington DC and Brightline to name a few.
