Role Description - Ship ML-powered product features end-to-end: - design, implement, test, deploy, and operate customer-facing functionality that uses ML. - Build application and service layers around models: - implement APIs, services, and workflows that handle model inputs/outputs, versioning, fallbacks, and edge cases. - Partner with Data Science to productionize models: - turn prototypes into robust, measurable, maintainable production systems. - Own production quality: - monitoring/alerting, debugging, incident response, performance tuning, and cost/latency optimization for ML-enabled services. - Develop validation and QC processes: - implement automated testing, evaluation harnesses, and regression checks to ensure system and model behavior remains correct over time. - Contribute to internal tooling: - improve developer experience through shared libraries, templates, CI/CD improvements, and automation that accelerates ML iteration. - Work on complex optimizer/core logic when needed: - contribute to algorithmic and performance-critical code paths with a focus on correctness and efficiency. - Lead through influence: - drive technical design, code quality, and best practices; collaborate cross-functionally with Product and Engineering. Qualifications - 8+ years software engineering background shipping production services and customer-facing features. - Solid systems experience: API design, reliability, observability, scalability, performance, and secure engineering practices. - Experience integrating machine learning into applications (e.g., model serving, batch scoring, feature pipelines, embeddings/vector workflows, model versioning). - Comfort working with data-intensive systems (large datasets, pipelines, data quality checks). - Ability to work across functions—translating ML behavior and constraints into product requirements and robust implementations. - Ownership mindset in an ambiguous, fast-moving environment. Requirements - Experience building internal platforms/tools for ML teams (evaluation pipelines, deployment automation, experiment tracking, guardrails). - Experience with optimization, routing/scheduling, or other algorithm-heavy domains. Company Description OneRail is a leading omnichannel fulfillment solution pairing best-in-class software with logistics as a service to provide dependability and speed to help businesses meet their delivery promise. With a real-time connected network of 12 million drivers, OneRail matches the right vehicle for the right delivery so brands lower expenses and increase capacity to rapidly scale their businesses. This people-plus-platform approach features a 24/7 USA-based exceptions team who maintain a 98% on-time delivery rate. By optimizing fulfillment processes, reducing costs and improving order accuracy with store-shelf-to-doorstep visibility, OneRail is committed to empowering clients and improving the customer experience. OneRail was named to the Deloitte Technology Fast 500™ two years in a row, was ranked 19th in the 2025 FreightTech 25, named for the fifth year in a row to the FreightTech 100, was honored as one of Inc. magazine’s Best Workplaces 2023, was listed on Forbes’ lists of America’s Best Startup Employers for the last three years, was named to the Inc. 5000 two years in a row and was selected as the Last Mile Company of the Year for the 2024 SupplyTech Breakthrough Awards. To learn more about OneRail, visit OneRail.com.