Senior Software Engineer - Infrastructure, Machine Learning
Baton
- United States
- United States
À propos
is ’s in-house product development group focused on harnessing emerging technologies to redefine transportation and logistics. With $10B in freight under management, our technology reaches every part of the U.We design and ship category-defining software that enables Ryder and its 50,000+ customers—including some of the world’s most well-known brands—to plan and execute freight intelligently, efficiently, and cost-effectively. Our work includes everything from customer-facing software to the data platform that will power the next era of innovation at Ryder. Ryder acquired Baton in 2022 to power its next wave of digital products. We operate at startup speed, with Fortune 500 reach. Role:
Senior Software Engineer - Infrastructure Team:
Machine Learning Pod Job Type:
Full Time Remote Days:
Monday & Friday Office Days:
Tuesday, Wednesday, Thursday As a Senior Software Engineer within our Machine Learning Team, you will tackle complex challenges in distributed systems and ML operations to enhance our machine learning infrastructure. You’ll build scalable ML infrastructure from the ground up - supporting model deployment, distributed training, real-time inference, and more. You’ll be a key partner to the Data Science team, helping bring value to production quickly and reliably. This role requires a blend of advanced Python programming skills within production environments and expertise in distributed computing. Own Core ML Infrastructure: Build and scale distributed systems for ML training, serving, and inference. Design and implement real-time ML workflows that power core product features.
Implementation of Distributed Systems: 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.
Real-Time ML Workflow Enhancement: Improve real-time machine learning workflows to support dynamic decision-making and automate core operational processes.
Platform Level Ownership: Lead the development of ML Ops systems, including model deployment, monitoring, and experiment tracking. Architect and manage scalable feature stores for online and offline usage.
AI-Driven Optimization: Contribute to agentic AI systems for freight matching, ETA prediction, and load scheduling. Write production-grade Python that operates at scale, with reliability and performance top of mind. Collaborate across engineering and data science to turn models into resilient software systems.
Production Python Expertise: 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.
Machine Learning Operations: Hands-on experience with distributed training pipelines, model serving, and monitoring. Deep familiarity with SQL (OLTP & OLAP), feature engineering, and caching patterns.
5 to 8 years of backend or ML infrastructure experience. ~ Proven track record building production ML workflows at scale. ~ Experience in industry logistics, transportation, or freight is a bonus.
Long Term Cash Incentive Plans ~ Annual Company Bonus ~Hybrid Work Schedule ~ Comprehensive Health Coverage ~ Employee Stock Purchase Program (15% discount to market value) ~ Collaborative, Tech-Forward, Cozy Office environment in Hayes Valley
In addition to base salary, Baton's full-time employees are eligible for an annual company performance bonuses.
Have an immediate impact: With Ryder’s existing customer base of 50,000+ companies and an internal headcount of 43,000, the scale and impact of our products will be large and far-reaching, from day one.
Opportunity to grow and lead in a Fortune 500 company: Creative, fast-paced environment to solve impactful problems in Supply Chain:
Compétences linguistiques
- English
Avis aux utilisateurs
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