Shippo

1 month ago

Senior Software Engineer, Data Product

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Own backend services that power merchant-facing EDD predictions and internal data product experiences, including APIs, caching, contracts, and production reliability. Build and optimize high-throughput Python services and distributed systems, lead API/service decomposition and technical reviews, and deliver observability with actionable alerts and runbooks. Partner with Data Science to bring ML outputs into production, maintain feature pipelines for consistency, and contribute to MLOps foundations for deployment, versioning, and rollback.

Location: Canada

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Own backend services delivering EDD predictions to merchants and internal consumers, including APIs, caching, contracts, and production reliability.
•Build Python services for high-throughput, low-latency workloads and lead API design and service decomposition for data product surfaces.
•Partner with Data Science to bring model outputs into production by owning the API layer, serving infrastructure, and operational reliability.
•Build and maintain feature pipelines connecting offline training to online inference with emphasis on consistency and data quality.
•Establish reliability and observability: instrumentation, alerting, runbooks, incident response, and MLOps foundations like deployment patterns, versioning, rollback, and experiment tracking integration.

Key Requirements

•7+ years building production backend systems, including meaningful collaboration with data and/or ML teams.
•Deep Python backend skills with FastAPI (or equivalent async framework) and strong PostgreSQL fundamentals (schema design, query optimization, migrations).
•Hands-on experience with event-driven systems like Kafka and owning distributed systems end-to-end (design, launch, monitoring, iteration).
•Ability to ship safely to production (canary, shadow, A/B, versioning, rollback), especially for ML-backed systems.
•Comfort instrumenting production systems for key signals (latency, throughput, error rates) and ML-specific signals like drift and prediction quality.

Experience:E-commerceLogisticsShippingMLMLOps

Skills:OwnershipTechnical leadershipMentorshipCommunicationTrade-off analysis

Tech Stack:PythonFastAPIPostgreSQLKafkaAPIsMLMLOpsFeature pipelinesObservabilityInstrumentationDriftPrediction qualityLLMA/B testingCanaryShadowVersioningRollback

Company Brief

Shippo

Shippo provides a shipping API and multi-carrier shipping platform that helps e-commerce businesses compare rates, buy labels, track shipments, and automate returns across carriers to streamline fulfillment and reduce shipping costs.

Industry: Supply Chain Technology

Company Size: Large (251 to 1,000 employees)

Growth: Growth Stage Startup

Funding: Series D

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn

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Shippo

1 month ago

Senior Software Engineer, Data Product

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: Canada

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Own backend services delivering EDD predictions to merchants and internal consumers, including APIs, caching, contracts, and production reliability.
•Build Python services for high-throughput, low-latency workloads and lead API design and service decomposition for data product surfaces.
•Partner with Data Science to bring model outputs into production by owning the API layer, serving infrastructure, and operational reliability.
•Build and maintain feature pipelines connecting offline training to online inference with emphasis on consistency and data quality.
•Establish reliability and observability: instrumentation, alerting, runbooks, incident response, and MLOps foundations like deployment patterns, versioning, rollback, and experiment tracking integration.

Key Requirements

•7+ years building production backend systems, including meaningful collaboration with data and/or ML teams.
•Deep Python backend skills with FastAPI (or equivalent async framework) and strong PostgreSQL fundamentals (schema design, query optimization, migrations).
•Hands-on experience with event-driven systems like Kafka and owning distributed systems end-to-end (design, launch, monitoring, iteration).
•Ability to ship safely to production (canary, shadow, A/B, versioning, rollback), especially for ML-backed systems.
•Comfort instrumenting production systems for key signals (latency, throughput, error rates) and ML-specific signals like drift and prediction quality.

Experience:E-commerceLogisticsShippingMLMLOps

Skills:OwnershipTechnical leadershipMentorshipCommunicationTrade-off analysis

Tech Stack:PythonFastAPIPostgreSQLKafkaAPIsMLMLOpsFeature pipelinesObservabilityInstrumentationDriftPrediction qualityLLMA/B testingCanaryShadowVersioningRollback

Company Brief

Shippo

Industry: Supply Chain Technology

Company Size: Large (251 to 1,000 employees)

Growth: Growth Stage Startup

Funding: Series D

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn