Computer Vision Scientist

Candidate should be able to:
Manage the annotation of datasets via external vendors
Create and manage Kubernetes clusters of cloud-based CV products
Select and manage external vendors and dev teams to support our projects
Create mobile and cloud-based CNNs for object classification
Design, engineer, and manage our system architecture and data strategy
work with our internal engineering team to create new products
Use phone-based LiDAR as ground truth annotation for training sets
Train ML models to an approximate distance within images
understand and apply 2D and 3D mathematical concepts (linear algebra, matrix multiplication, quaternions, etc)

Candidate should have:
Experience Testing, diagnosing and fixing bugs
Experience building web apps, APIs, and SDKs
Capacity to prioritize tasks through self-directed time management and organization
Experience with Detectron 2, TensorFlow & TensorFlow3D, AlexNet, MXn...