Head of AI Research Product

About Via Via is on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners in 30+ countries, Via is recognized as the leading transportation technology and service provider for governments. Via’s platform has pioneered microtransit — a new mode of mass transit — and today offers a comprehensive, end-to-end public transit solution that helps our customers design, operate, and optimize their transit systems using software, services, and billions of proprietary real-world trip data points. The result: lower costs, equitable access, and better passenger experiences.

Via

How cities connect.

Public transitTransitTechMobility-as-a-ServiceDemand-responsive transportation (DRT)Government technologyGovTechMicrotransitOn-demand microtransitADA paratransitParatransit software

V

ridewithvia.com

501-1,000 employees

Software Development

New York, New York

2012

Privately Held

202k LinkedIn followers

Raised $887.1M

• Build and lead Via's AI research product function, defining the roadmap for how machine learning advances rider experience and transit network performance.
• Design and deploy reinforcement learning systems that optimize routing, pooling efficiency, and real-time dispatching, balancing rider satisfaction against vehicle utilization and transit agency cost targets.
• Pioneer AlphaGo-style machine learning for transit: combine deep reinforcement learning, and tree search over high-fidelity simulations of real transit networks, training policy and value networks that discover dispatching, pooling, and network-design strategies beyond what hand-built heuristics or conventional optimization can reach.
• Develop weighted ensemble models and multi-objective optimization frameworks that surface the right tradeoffs between competing system goals: wait times, cost per ride, emissions, and equity of service.
• Invent personalization systems that adapt the rider mobile experience in real time, surfacing relevant trip options, proactive alerts, and dynamic pricing signals, in close partnership with the rider mobile product team.
• Research and productize behavioral incentive models that increase ridership and shift demand to improve aggregation: surge smoothing mechanisms, loyalty structures, and gamified engagement grounded in behavioral economics and causal inference.
• Partner with lighthouse transit agencies to co-develop and validate novel AI approaches, turning field pilots into scalable platform features.
• Establish rigorous experimentation infrastructure (A/B testing, contextual bandits, offline policy evaluation) to measure the real-world impact of model changes on rider behavior and agency outcomes.

• MS or PhD in a quantitative field: machine learning, operations research, statistics, applied mathematics, or a related discipline.
• Deep hands-on proficiency in ML: reinforcement learning, supervised and unsupervised methods, probabilistic modeling, and optimization. Experience with AlphaGo-style approaches (self-play, Monte Carlo tree search, policy/value networks) and with large-scale real-time inference systems is a strong plus.
• Genuine user empathy: you think as carefully about what a rider or agency dispatcher experiences as you do about model architecture.
• Very user-minded and clear-eyed about outcomes for users. You work closely with the mobile and SaaS product teams on experimentation, and you know how to find the balance between a delightful user experience and service KPIs such as efficiency and rider experience.
• Business sense and product instincts: you know how to translate a research finding into a shipped product and a shipped product into a business outcome.
• Experience partnering with engineering teams to move models from research into production at scale.
• Track record of working with external customers or partners to iterate on novel solutions in ambiguous, real-world conditions.
• Comfort operating across research, product, and commercial contexts: you can present a model architecture to an ML engineer and a product strategy to a transit authority CEO.
• Passion for building technology that makes public transit work better for everyone, especially riders in underserved communities.

• Final salary will be determined by the candidate’s experience, knowledge, and skills. Salary reflected does not include equity or variable pay, where applicable
• Salary Range: $250,000 - $310,000 per year
• Comprehensive health coverage, with low-cost dental and vision plans
• A 401(k) with a generous company match and vesting
• Fully paid parental leave for new parents, with extended leave options
• Additional benefits (mental health, pet insurance, and other wellness perks)
• 20 days of paid time off (PTO) annually