SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 170,000 - 220,000 / annual
Via is building the technology backbone for modern public transportation systems globally, serving hundreds of agency partners. The company transforms antiquated transit networks into smart, data-driven digital systems focused on access, equity, and sustainability.
As a Senior Software Engineer on the Remix team, you will own features end-to-end from concept to production, shaping both what the team builds and how it builds. You'll work on planning and scheduling products used by some of the world's largest transit networks, involving optimization, geospatial computation, machine learning, and AI.
Key responsibilities include:
- Improving planning and scheduling products to help transit planners explore concepts, make data-informed decisions, and deliver better service to riders
- Building, scaling, and improving optimization and backend systems; ensuring they run fast and reliably in production
- Collaborating with designers, data scientists, algorithm researchers, product managers, in-house transit planners, and customers
- Working across a diverse tech stack (Python, Ruby, TypeScript, React) to deliver strong end-to-end user experiences
- Contributing to engineering best practices and architecture discussions within your area of expertise
- Building and maintaining processes and tools to maintain high productivity and code quality
The team values strong engineering fundamentals and a user-centered approach to product development. You'll have the opportunity to work on computationally complex problems at scale.
Requirements:
- Minimum 5 years of professional software engineering experience
- Demonstrated experience building and scaling a computationally hard system in production (optimization, routing, search, simulation, or geospatial processing)
- Mission-driven mindset; passion for companies with strong values
- User-centric approach; comfort engaging with customers to understand core needs
- Effective use of AI tools in day-to-day engineering work
- Collaborative, humble, empathetic, and feedback-driven working style
- Plus: experience with operations research, mathematical optimization, or applied machine learning
- Plus: experience with geospatial data, mapping technologies, or data visualization
