Computer Vision Engineer

Blissway Inc., Denver, Colorado

What you will do

Own the Model: Data collection, dataset curation, design, training, and evaluation. Your job is making sure the model is correct, working closely with our MLOps Engineer to get it to production.
Vision at Real Scale: 11 million images a day across vehicles, license plates, axles (so we classify each vehicle correctly), and lane markings. At this volume, the right model can drastically improve accuracy and cut cost at the same time.
Classical CV to Custom SOTA: Our toolbox spans traditional computer vision algorithms through custom-trained state-of-the-art models. You pick the right tool, and if nothing off the shelf is good enough, you design and train your own.

All jobs

Computer Vision Engineer

Blissway Inc., Denver, Colorado

Posted pay

$140K–$195K

a year

Compared with similar jobs

This base pay is below the median for ML and AI engineering jobs in other US places with no level in the job title.

Median: $183K a year
Other jobs in the group: 416

We compare the middle of each posted range. This is base pay as posted. The group does not include this job.

Location: Denver, Colorado
Work type: Hybrid
Level: Not given
Experience: 2+ years
Skills in the job text: Python
Posted: Sep 4, 2026
Last check: 48 min ago
Job type: ML / AI engineering, Inference & ML systems

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Blissway Inc.

Open tech jobs: 9
With posted pay: 100%
Median posted base: $135K–$180K

About Blissway Inc.: funding, hiring and pay

Blissway Inc.

About Blissway Inc.: funding, hiring and pay

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What you will do

Own the Model: Data collection, dataset curation, design, training, and evaluation. Your job is making sure the model is correct, working closely with our MLOps Engineer to get it to production.
Vision at Real Scale: 11 million images a day across vehicles, license plates, axles (so we classify each vehicle correctly), and lane markings. At this volume, the right model can drastically improve accuracy and cut cost at the same time.
Classical CV to Custom SOTA: Our toolbox spans traditional computer vision algorithms through custom-trained state-of-the-art models. You pick the right tool, and if nothing off the shelf is good enough, you design and train your own.

What you need

You are a good fit if

You love the grind: You take ownership and put in the time to meet deadlines. Our recent team survey showed an average of 55 hours/week, with occasional 70+ hour bursts for major releases.
You are detail obsessed: You have experience writing code, designing or building systems that stands up to the unpredictability of the physical world, where the small details are the difference between success and failure.
You are adaptable: We are a lean team. If you only want to work on a "niche thing" or are uncomfortable helping other teams when they need a boost, this isn't the place for you. We expect you to figure out what you need to get stuff done.
You code really well: We mostly use Python and TypeScript, but we don’t care what you’re most proficient in today—as long as you learn fast.
You value working together in person: You’re excited to work alongside the team at our Denver office. This role is in-office on Mondays, Wednesdays, and Fridays, with flexibility to work remotely on Tuesdays and Thursdays.

The Mission: Every image on our system has one job: complete an accurate toll transaction through our billing system. Your job is making that transaction more accurate. We process 11 million images a day, using detection, segmentation, classification, embeddings, and re-identification to match each vehicle to its toll. You'll find where our models fall short, decide what to fix first, and build the fix, from dataset curation to custom state-of-the-art architectures. This role is for the engineer who reads a new paper and immediately wants to know if it works in the real world.

Requirements

Experience: 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.
Real CV Depth: Experience with modern computer vision and the judgment to know when a classical technique beats a heavy model. You're not reaching for a transformer when a filter will do.
Hands-On Training: You've trained, fine-tuned, and debugged models on real-world, custom data, not just benchmark datasets.
Strong Engineering: You write clean, production-quality code. Experience shipping models to production is a strong plus, but if you're coming from research, show us code you've built that others actually use.
Python: Fluent in Python and its ML ecosystem.
Bonus: Experience optimizing models for edge hardware, or working on vehicle detection, license plate recognition, tracking, or poor lighting and weather conditions.

Computer Vision Engineer

What you will do

Computer Vision Engineer

What you will do

What you need

You are a good fit if

Requirements

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