Hopper

Full-stack Engineer

• Identify and execute improvements to the codebase that make it easier for both humans and AI agents to move fast and ship safely.
• Work with a group of senior engineers in a low-process environment powered by trust and autonomy.
• Drive decisions and consensus asynchronously with thoughtful documentation and specs.
• Build new features from top to bottom — from UX to database. Ship fast. Learn fast. Repeat.
• Architect scalable solutions and foundational patterns that let us efficiently launch new partner experiences.
• Work directly with PMs and business partners to define and refine our roadmap. Your voice and technical vision matter.
• Collaborate with a diverse group of people, giving and receiving feedback for growth.

Senior Full Stack Product Engineer

• Identify and implement improvements to the codebase to enable humans and AI agents to deliver quickly and safely.
• Collaborate with a group of senior engineers in a lightweight, trust-based, autonomous environment.
• Drive decisions and achieve consensus asynchronously through rigorous documentation and specifications.
• Build new features end-to-end — from user experience (UX) to the database. Deliver, learn, and iterate rapidly.
• Design scalable solutions and foundational models to efficiently launch new partner experiences.
• Work directly with product managers (PMs) and business partners to define our roadmap. Your technical voice and vision matter.

Senior Full-Stack Product Engineer

Backend Engineer

• Design, build and operate a public API.
• Operate autonomously but work closely with your fellow engineers as well as designer/PM to ensure high alignment.
• Explore engineering improvements for the team and the product.
• Collaborate cross-functionally with the product team, other Hopper teams and external partner teams.
• Our group operates with very few meetings and emphasizes strong alignment and asynchronous decision making.

Senior Backend Engineer – API

Product Manager

• Define what the HTS API Marketplace is: how capabilities are structured, packaged, and priced across a portfolio spanning HTS Connect, Search Polygons, Autocomplete, Ranking, Content & Property Mapping, Room Mapping, Deduplication/Auction, Pricing, Extranet, Taxes, and Custom Deals Engine.
• Coordinate with capability PMs — who own the underlying technical systems — to understand each capability's roadmap, constraints, and customization surface, and translate that into externally-consumable API products.
• Own the commercial model for the marketplace: platform vs. variable fee decisions, take rate structure per capability, enterprise packaging, and the custom deals framework for large partners with differentiated customer segments.
• Build the developer and partner experience from scratch: API specifications, partner onboarding flows, documentation standards, sandbox environments, and integration tooling that minimizes time-to-first-value.
• Use AI tools and rapid prototyping to test ideas quickly — mock API responses, prototype partner portals, simulate pricing and ranking configurations — before committing engineering resources.
• Establish the go-to-market motion for the marketplace: work with Commercial to identify the right partners for each capability, sequence launches, and define what a successful commercial rollout looks like.
• Own the marketplace revenue P&L: model and track GBV, take rate, and per-capability unit economics in partnership with Finance.
• Set the sequencing and prioritization across all capabilities — from in-progress work (HTS Connect, Taxes) through scoping-stage products (Content & Property Mapping, Room Mapping, Deduplication/Auction, Pricing) to capabilities not yet started (Search Polygons, Autocomplete, Ranking, Extranet, Custom Deals Engine).

Principal Product Manager, HTS API Marketplace

Principal Product Manager – HTS API Marketplace

• Define what the HTS API Marketplace is: how capabilities are structured, packaged, and priced across a portfolio spanning HTS Connect, Search Polygons, Autocomplete, Ranking, Content & Property Mapping, Room Mapping, Deduplication/Auction, Pricing, Extranet, Taxes, and Custom Deals Engine.
• Coordinate with capability PMs — who own the underlying technical systems — to understand each capability's roadmap, constraints, and customization surface, and translate that into externally-consumable API products.
• Own the commercial model for the marketplace: platform vs. variable fee decisions, take rate structure per capability, enterprise packaging, and the custom deals framework for large partners with differentiated customer segments.
• Build the developer and partner experience from scratch: API specifications, partner onboarding flows, documentation standards, sandbox environments, and integration tooling that minimizes time-to-first-value.
• Use AI tools and rapid prototyping to test ideas quickly: mock API responses, prototype partner portals, simulate pricing and ranking configurations — before committing engineering resources.
• Establish the go-to-market motion for the marketplace: work with Commercial to identify the right partners for each capability, sequence launches, and define what a successful commercial rollout looks like.
• Own the marketplace revenue P&L: model and track GBV, take rate, and per-capability unit economics in partnership with Finance.
• Set the sequencing and prioritization across all capabilities: from in-progress work (HTS Connect, Taxes) through scoping-stage products (Content & Property Mapping, Room Mapping, Deduplication/Auction, Pricing) to capabilities not yet started (Search Polygons, Autocomplete, Ranking, Extranet, Custom Deals Engine).

• Design, build and operate a public API
• Operate autonomously but work closely with your fellow engineers as well as designer/PM to ensure high alignment
• Explore engineering improvements for the team and the product
• Collaborate cross-functionally with the product team, other Hopper teams and external partner teams
• Our group operates with very few meetings and emphasizes strong alignment and asynchronous decision making.

• **About the Team**
• Hopper's Fintech Foundation team sits at the centre of the company's mission: reshaping how more than 100 million monthly active users experience travel. It owns the pricing engine that balances customer demand against financial risk across dozens of partners — including Capital One, Air Canada, and Spirit Airlines. As an ML engineer on this team, you will directly shape how Hopper prices ancillary products in real time and at scale.
• **About the Role**
• As a Software Engineer on the Fintech Foundation team, you will design, build, and evolve the machine learning systems that power Hopper's pricing engine. Your work will have direct impact on revenue, financial risk management, and the customer experience across the full partner portfolio.
• You will work closely with the Data Science, Engineering, and Product teams to deliver pricing solutions that are reliable, scalable, and oriented toward commercial outcomes.
• ****What would your day-to-day look like**
• - Design and implement automated, reusable training pipelines to ensure consistent, scalable model delivery across the partner portfolio
• - Build ETL pipelines with thoughtful feature engineering to guarantee clean, reliable inputs for pricing models
• - Develop and deploy real-time ML pricing solutions to production, owning the full path from model to live environment
• - Monitor production systems for latency, drift, and training-serving skew, optimising continuously to maintain model integrity
• - Run champion-challenger tests on pricing and product construction levers to surface improvements and respond to shifting market conditions
• - Partner with data scientists, engineers, and product stakeholders to translate business needs into well-scoped technical solutions
• **An ideal candidate has**
• - 5+ years of experience in a similar role, ideally within production ML systems or large-scale pricing platforms
• - Proficiency in Python, Scala, and SQL, applied to production ML systems rather than exploratory work
• - Experience in data modelling, software architecture, and distributed data processing frameworks at scale
• - Deep understanding of ML algorithms and when to apply them in the context of pricing, demand forecasting, or similar commercial domains
• - Strong analytical instincts and attention to detail, with a track record of catching issues before they reach production
• - A product mindset that keeps the customer outcome in view, even when the work is deeply technical
• - Clear, collaborative communication skills that hold up across data science, engineering, and business stakeholder audiences
• **Perks and Benefits of working with us **
• - Well-funded and proven startup with large ambitions, competitive salary and the upsides of pre-IPO equity packages.
• - Unlimited PTO.
• - Carrot Cash travel stipend.
• - Access to co-working space on demand through FlexDesk AND Work-from-home stipend.
• - Please ask us about our very generous parental leave, much above industry standards!.
• - Entrepreneurial culture where pushing limits and taking risks is everyday business.
• - Open communication with management and company leadership.
• - Small, dynamic teams = massive impact.
• - 100% employer paid Medical, Dental and Vision coverage for employees.
• - Access to Disability & Life insurance.
• - Health Reimbursement Account (HRA).
• - DCA/ FSA and access to 401k plan.

Senior Software Engineer – AI Fintech

• Design and implement automated, reusable training pipelines to ensure consistent, scalable model delivery across the partner portfolio
• Build ETL pipelines with thoughtful feature engineering to guarantee clean, reliable inputs for pricing models
• Develop and deploy real-time ML pricing solutions to production, owning the full path from model to live environment
• Monitor production systems for latency, drift, and training-serving skew, optimising continuously to maintain model integrity
• Run champion-challenger tests on pricing and product construction levers to surface improvements and respond to shifting market conditions
• Partner with data scientists, engineers, and product stakeholders to translate business needs into well-scoped technical solutions