Software Engineer, Vehicle Identification

Work at Blissway: Opportunity for Impact Every Day 🚀✨

Blissway is a startup that simplifies toll collection and dramatically improves highway safety. We are multiple startups in one: Deep Tech, AI/ML, Hardware, SaaS, and IoT. For the past five years, we have built a nearly insurmountable technological lead in tolling, an industry that is quietly bigger than football. While our competitors have thousands of employees, we operate with a lean but growing team of less than 30. We’ve stayed under the radar, but our impact is visible on the massive Interstate Highway System connecting every major US metro (except Juneau, AK—sorry, Juneau).

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 50 hours/week, with occasional 70+ hour bursts for major releases.

• You are detail obsessed: You have experience writing code that stands up to the unpredictability of the physical world, where the small details are the difference between success and failure.

• You are adapatable: 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.

Our Technical Ecosystem: While we value problem-solving over specific syntax, you’ll likely spend your time working with:

• Languages: Python, TypeScript, C++, SQL.

• Frameworks and Tools: NestJS, Node.js, FastAPI, PostgreSQL, MongoDB, Redis, Next.js, Tailwind CSS, React, Sentry.

• Infrastructure: AWS, Docker, Linux, IoT Edge Devices.

• Specialties: Computer Vision (OpenCV), ML Integration, Payment Processing.

Software Engineer, Vehicle Identification

The Mission: The ID team’s job is to accurately extract data from the images our roadside equipment captures: license plate number, plate state, lane, axle count, and more. That data drives billing. Accuracy and speed are the competitive moat.

The Work:

• The Identification Engine: Own the core logic that decides what happens with each transaction, enabling us to identify cars on the road. You are detail-oriented enough to care about the difference between a 99.95% and 99.97% accuracy rate and creative enough to want to close that gap through data driven testing.

• Human Review Infrastructure: You are comfortable working across the stack to own debugging and updates. The backend refactor will require frontend coordination. You don’t stop at the interface boundary, you drive forward to a solution.

• Strategy Locus: Collaborate with the ML team to request, test and implement models that increase identification reliability. speed. Partner with the data analyst to understand where the strategy is failing and why.

• Massive Throughput: Scale our capabilities from thousands to millions of cars daily. You will encounter older designs that didn’t scale. You will help us rearchitect them for growth.

Requirements:

• Education: MS or BS in Computer Science or a related technical field.

• Mindset: You are excited to work at a startup and be part of a core engineering team.

  • You don't wait for a manual or a step-by-step guide; you figure out what you need to get stuff done and you do it with a professional, "owner" mentality.

  • You understand that in a small team, feedback is the fastest way to level up and you welcome it.

  • You think in systems, not features. You understand that a change to one part of the system will impact users in other parts and you account for that.

  • You are genuinely flexible. When the embedded team needs a hand, you help. When a project priority shifts, you shift.

• Denver: As a Denver based team, we are looking to hire someone who understands the value of in person collaboration and is excited by the occasional late night on the highway calibrating equipment.

  • While we have a hybrid work model, some roles are simply most effective in person. Our typical schedule is 3-4 days in office per week, and 1-2 days