Flock Safety is looking to architect and deploy large-scale, real-time, and accurate multi-object tracking solutions to reduce crime in the United States by 25% in the next three years.
Requirements
- 5+ years of industry experience in Deep Learning and Computer Vision
- Experience with Computer Vision modeling, such as Object Detection, Multi-Object Tracking, etc.
- Experience in metric learning, contrastive learning, and embedding-based ReID models
- Experience with integrating tracking algorithms like SORT, DeepSORT, ByteTrack, FairMOT, or graph-based tracking into systems
- Knowledge of probabilistic models (e.g., Kalman Filters, Bayesian filtering) and trajectory prediction
- Strong experience in Python
- Experience with SQL
- Basic Git knowledge
- Basic Bash knowledge
Responsibilities
- Architect and deploy large-scale, real-time, and accurate multi-object tracking solutions
- Work closely with research scientists, ML engineers, infrastructure teams, and operations to develop high-performance systems for tracking people, vehicles, or other objects
- Develop and integrate tracking algorithms like SORT, DeepSORT, ByteTrack, FairMOT, or graph-based tracking into systems
- Work on tracking tickets and own experiments
- Monitor performance in production and perform small improvements to R&D environment
Other
- Meet the team & cross-functional stakeholders
- Understand the systems and processes in place that Engineering uses, and leverage them to produce additional value
- Lead projects from R&D to production
- Flexible PTO, fully-paid health benefits plan for employees, family leave, fertility & family benefits, Spring Health, caregiver support, Carta Tax Advisor, ERGs, WFH stipend, productivity stipend, home office stipend
