Baton is looking to redefine transportation and logistics by building category-defining software that enables intelligent, efficient, and cost-effective freight planning and execution. The Senior Software Engineer - Infrastructure will help build and scale the ML infrastructure to support model deployment, distributed training, and real-time inference, ultimately enabling supply chain on autopilot.
Requirements
- Advanced Python proficiency in large-scale production environments.
- Experience building scalable backend or ML infrastructure using distributed computing techniques.
- Strong background in AWS and cloud-native data/compute services.
- Hands-on experience with distributed training pipelines, model serving, and monitoring.
- Deep familiarity with SQL (OLTP & OLAP), feature engineering, and caching patterns.
- Proven track record building production ML workflows at scale.
- 5 to 8 years of backend or ML infrastructure experience.
Responsibilities
- Build and scale distributed systems for ML training, serving, and inference.
- Design and implement real-time ML workflows that power core product features.
- Build robust distributed systems tailored for efficient ML training and seamless operational deployment.
- Streamline and manage both online and offline feature stores, optimizing feature engineering processes for greater efficiency.
- Improve real-time machine learning workflows to support dynamic decision-making and automate core operational processes.
- Lead the development of ML Ops systems, including model deployment, monitoring, and experiment tracking.
- Write production-grade Python that operates at scale, with reliability and performance top of mind.
Other
- Hybrid Work Model
- Remote Days: Monday & Friday
- Office Days: Tuesday, Wednesday, Thursday
- Collaborate across engineering and data science to turn models into resilient software systems.
- Experience in industry logistics, transportation, or freight is a bonus.
