Principal Product Manager, Rides Matching

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Overview We are looking for a Principal Product Manager to join the Rides team at Bolt. You have coordinated cross-functional product pods and have experience working across organisational boundaries, including negotiating interface contracts and mutual accountability with adjacent teams such as pricing or economics.

You have direct exposure to reinforcement learning in production, or have worked with teams that deployed RL systems, with a solid grasp of reward design, exploration-exploitation trade-offs, and the gap between simulation and live environments. Connect with colleagues at annual company events and smaller team gatherings.

In this role, you will be accountable for defining and executing the product strategy for our matching and dispatching engine, the core system linking rider demand to driver supply in real time.

You will work on one of the highest-impact areas in the marketplace, delivering structural improvements that shape rider experience, driver earnings, and overall platform efficiency at scale.

Main tasks and responsibilities Define the product strategy and roadmap for the dispatching engine, sequencing foundational ML/RL investments alongside near-term improvements to queue ranking, dispatch strategy, and retry governance.

Coordinate the productionisation of machine learning and reinforcement learning models, from offline training through shadow mode, A/B testing, incremental rollout, and live monitoring across multiple markets.

Own and improve the performance of the existing matching stack while the new engine is being built, maintaining stability and delivering incremental efficiency gains. Define and maintain the signal contract between matching and pricing, ensuring matching delivers reliable, low-latency completion probability and supply density signals.

Design experiments, evaluate results, and translate complex algorithmic trade-offs into clear recommendations for senior stakeholders and cross-functional peers. Set priorities and resolve trade-offs within a cross-functional pod spanning product, engineering, data science, and specialist roles, acting as the accountable owner for matching KPIs.

About you You have experience shipping machine learning models into production systems that serve real-time allocations at scale, including ownership of the full lifecycle from feature engineering and training through shadow deployment, monitoring, and iteration.

You have worked on allocation, matching, dispatch, or equivalent real-time systems in a two-sided marketplace, logistics platform, or high-throughput environment, with a strong grasp of supply-demand dynamics and global versus local optimisation trade-offs.

You have navigated the complexity of maintaining a live production system while simultaneously building its replacement, with a track record of keeping current performance stable through a migration.

You are able to move fluently between detailed statistical evaluation and clear stakeholder communication, and you produce high-quality written deliverables including strategy documents, technical specifications, and experiment reviews. Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.

Take care of your physical and mental health with our wellness perks. Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge. Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days. #J-18808-Ljbffr