Senior Software Engineer - Infrastructure, Machine Learning (San Francisco)

Senior Software Engineer - Infrastructure, Machine Learning

Baton is Ryder'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.S. economy.

We design and ship category-defining software that enables Ryder and its 50,000+ customersincluding some of the world's most well-known brandsto 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.

Baton's mission : enable supply chain on autopilot.

Ryder acquired Baton in 2022 to power its next wave of digital products. We operate at startup speed, with Fortune 500 reach. If you have a passion for solving complex problems and creating impact for the engine of the American economy, you'll love it here.

Role : Senior Software Engineer - Infrastructure Team : Machine Learning Pod Location : Hayes Valley, San Francisco, CA

Job Description

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.

Responsibilities

• Own Core ML Infrastructure :

Build and scale distributed systems for ML training, serving, and inference.

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.

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.

Required Qualifications

Advanced Python proficiency in large-scale production environments.

Experience building scalable backend or ML infrastructure using distributed computing techniques.

Hands-on experience with distributed training pipelines, model serving, and monitoring.

Preferred Qualifications

The Perks

Compensation Range : The annual base salary range for this position is $200,000 - $250,000

Compensation will vary based on factors including skill level, transferable knowledge, and experience. Note that the above is not the representation of total compensation, which includes our LTI Package as well. In addition to base salary, Baton's full-time employees are eligible for an annual company performance bonuses.

Why You Should Join

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.

You'll get to work in a rapidly growing, startup-like environment while having the stability and backing of Ryder and its full executive team.

We're going to design completely new tools for an industry that hasn't been rethought in decades. And to do this, we need people who think differently.