product manager for rides matching

Bolt is a global mobility platform used by more than 200 million customers and 4.5 million driver and courier partners across 50 countries. Its services include ride-hailing, food delivery, scooters, e-bikes, and car-sharing.

• Define the product strategy and roadmap for the dispatching engine, balancing foundational ML/RL investments with 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 existing matching stack, maintaining stability and delivering incremental efficiency gains while the new engine is being built
• Define and maintain the signal contract between matching and pricing, ensuring matching provides reliable, low-latency completion probability and supply density signals
• Design experiments, evaluate results, and translate 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; own matching KPIs

• Experience shipping machine learning models into production systems serving real-time allocations at scale, including the full lifecycle from feature engineering and training through shadow deployment, monitoring, and iteration
• Experience with allocation, matching, dispatch, or equivalent real-time systems in a two-sided marketplace, logistics platform, or high-throughput environment; strong understanding of supply-demand dynamics and global versus local optimisation trade-offs
• Experience maintaining a live production system while building its replacement, with a track record of keeping current performance stable through a migration
• Experience coordinating cross-functional product pods and working across organisational boundaries, including negotiating interface contracts and mutual accountability with adjacent teams such as pricing or economics
• Ability to move between detailed statistical evaluation and clear stakeholder communication; strong written deliverables, including strategy documents, technical specifications, and experiment reviews
• Direct exposure to reinforcement learning in production, or experience working with teams that deployed RL systems; understanding of reward design, exploration-exploitation trade-offs, and the gap between simulation and live environments
• **Nice to have:** None specified

• Stock options
• Wellness perks
• A 1-month paid sabbatical after 5 years at Bolt
• Annual company events and smaller team gatherings
• Hybrid model with at least 12 monthly in-office days
• Some perks may differ depending on location and role
• AI use in daily work is expected; employees remain responsible for the output and must maintain a high standard