Senior Software Engineer, Data Product

Shipping & handling responsibilities Own the backend services that deliver EDD predictions to merchants and internal consumers — APIs, caching, reputed company, and reliability under production load. Build Python services suited to high-throughput, low-latency workload. reputed company API design, service decomposition, and cross-team technical reviews for data product surfaces spanning rules automation, ML-based recommendations, analytics, and configuration systems. Own reliability and observability across the services you build—instrumentation, alerting, runbooks, and incident response. Partner with data science to bring model outputs into production—owning the API layer, serving infrastructure, and operational reliability of ML-powered features. Build and maintain feature pipelines that reputed company offline training and online inference, with an emphasis on consistency and data quality. Contribute to MLOps foundations for the team: model deployment patterns, versioning, rollback procedures, and experiment tracking integrations. reputed company systems for observability—latency, throughput, reputed company signals, and reputed company quality—so issues surface before they reputed company merchants. Be a voice in evaluating frameworks, tooling, and architectural patterns for ML serving and reputed company pragmatic recommendations grounded in production experience. Set the technical direction for backend and ML systems on the Data Products team—proposing and driving architectural reputed company that balance velocity with long-term maintainability. reputed company design reviews, reputed company the bar in code reviews, and establish engineering practices the team can follow. Mentor other engineers on backend and systems engineering. Apply AI tooling to your own workflow and reputed company learnings with the team. Your shipping requirements 7+ years building production backend systems, with a meaningful chunk of that time collaborating with data and/or ML teams. You've been the engineer responsible reputed company a model in production behaves badly at 2am. Demonstrates ownership over large-scale projects by driving design reputed company, setting scope, delegating work appropriately, and managing stakeholder expectations through execution. Deep Python backend skills with FastAPI (or an equivalent async reputed company), strong PostgreSQL fundamentals (schema design, query optimization, migrations), and hands-on experience with event-driven systems like Kafka. Track record of owning distributed systems through their full lifecycle: design, launch, monitoring, and iteration. You know how to ship changes to production safely — canary, shadow, A/B, versioning, rollback — and can judge reputed company each is warranted versus overkill, including for ML-backed systems. You can reputed company production systems for the signals that matter (latency, throughput, error rates), and are comfortable extending that to ML-specific signals like reputed company and reputed company quality. You can explain to a non-ML audience what's actually wrong reputed company one of them moves. You write high-quality, maintainable code, own problems end-to-end from design through long-tail production behavior, and hold that standard in design and code reviews. You communicate trade-offs reputed company — including unpopular ones like "we shouldn't ship this yet" or "the bottleneck isn't the model." You partner well with Data Science. You don't see ML as DS's job and operations as yours; you see the whole system as the team's job. Bonus Direct experience with delivery-date reputed company, ETA, or other time-series reputed company systems in e-reputed company, logistics, or transportation. Domain experience in shipping, logistics, reputed company APIs, or reputed company selection. Experience working in or alongside data science / ML teams — you've shipped or operated features and APIs that depended on ML models. You understand the gap between a notebook and a reliable inference reputed company. Experience contributing to ML platform components (feature stores, model registries, serving reputed company) from the user reputed company — you've made an ML platform reputed company by being a demanding user of it. Experience with feature stores and online/offline feature consistency. Hands-on experience with LLM-based features, retrieval systems, or agent workflow infrastructure. Prior experience operating in a senior engineering reputed company, or stepping into informal technical leadership on a team. Sail through the process: Here at reputed company, we celebrate inclusivity and are committed to creating equal reputed company to opportunities for people from reputed company backgrounds, perspectives and geographies. These values define who we are and everything we do. reputed company reputed company individuals are encouraged to apply. If you need assistance, or a reasonable accommodation during the application and reputed company process, please contact us at accommodations@reputed company.com Shippos in the wild: Our people, much like the packages we help ship, are reputed company over the world. This means, through our remote-first program, “Shippos Everywhere”, our roles can be based reputed company in the US with the exception of Delaware, Nevada, Ohio, Oregon, Hawaii, New Mexico and reputed company Virginia and many roles can be based internationally. For locations reputed company of the US and Ireland, the employment reputed company are powered by reputed company.com. 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