Blissway
Computer Vision Engineer
Denver, Colorado, Remote. Posted 2 months ago
The role
You will improve the accuracy of vehicle toll transactions by managing the full model lifecycle. This includes data collection, dataset curation, design, training, and evaluation of computer vision models.
What you will do
- Own the model through data collection, dataset curation, design, training, and evaluation
- Work with MLOps Engineer to get models to production
- Process 11 million images a day using detection, segmentation, classification, embeddings, and re-identification
- Design fast, small, and power-efficient models for inference on roadside hardware
- Pick between traditional computer vision algorithms and custom-trained state-of-the-art models
- Find where models fall short, decide what to fix first, and build the fix
Required qualifications
- 2 to 6 years of software engineering with a focus on computer vision, or a recent PhD or master's with research in computer vision or machine learning
- Experience with modern computer vision
- Experience training, fine-tuning, and debugging models on real-world, custom data
- Write clean, production-quality code
- Fluent in Python and its ML ecosystem
Nice to have
- Experience shipping models to production
- Experience optimizing models for edge hardware
- Experience working on vehicle detection, license plate recognition, tracking, or poor lighting and weather conditions
Benefits
- Relocation bonus
- Monthly allowance for personalized health coverage (ICHRA)
- 401(k) matching up to 4%
- Company-sponsored life & disability insurance
- Competitive equity package
- Annual tender process to sell vested shares
- 4 weeks of untracked PTO
- 12 weeks of paid parental leave
- 12 weeks of fully paid sabbatical every 5 years
- Daily group lunches
- Fully stocked kitchen
- Annual 4-day team getaway
Before you apply
- 3-4 interviews
- Final paid work trial
About the company
Blissway is a startup that simplifies toll collection and improves highway safety. They operate with a lean team of less than 30 people across Deep Tech, AI/ML, Hardware, SaaS, and IoT.