Software Engineer - Infrastructure, Machine Learning
San Francisco, California, United States
Full Time Mid-level / Intermediate USD 162K - 216K
Baton Trucking
Baton is a technology innovation lab for Ryder and formerly a technology startup focused on eliminating waste in supply chains.Who We Are
Baton is seeking ambitious individuals who desire the autonomy and agility of a startup environment combined with the backing, power, reach, and stability of a highly respected logistics industry giant.
Baton is the Silicon Valley-based technology innovation lab for Ryder, a leading logistics company that owns 260k trucks and manages $7.4B of freight.
Prior to the September 2022 acquisition, Baton was a venture-backed start-up that operated a fleet of trucks and hung out at truck stops to truly understand the challenges at hand.
The Problem We’re Solving
Our mission is to enable supply chain on autopilot.
There are 500 million hours wasted in trucking each year, over 3 billion gallons of fuel wasted per year from trucks idling, and 1 in 5 trucks on the road driving empty at any given point.
This has a massive impact on the environment, the lives of millions of drivers, and ultimately, the cost of goods that we all pay. Baton is fixing this, and you will too through the impactful work you’ll do here.
Location: Hayes Valley, San Francisco, CA
Role: Software Engineer - Infrastructure
Team: Machine Learning Pod
Job Type: Full Time
Work Model: Hybrid
Remote Days: Monday & Friday
Office Days: Tuesday, Wednesday, Thursday
Job Description
As a Software Engineer specializing in Infrastructure for Machine Learning, you will tackle complex challenges in distributed systems and ML operations to enhance our machine learning infrastructure. This role requires a blend of advanced Python programming skills within production environments and expertise in distributed computing.
As a Software Engineer on our Machine Learning Pod, you will:
- Build a feature store for online inference
- Build realtime event listeners to react to changes to Load state
- Build dashboards and run analysis on historical Loads to determine model feasibility
Responsibilities
- Optimization of ML Architecture:
- Develop and refine data engineering and machine learning frameworks to boost scalability and enhance system performance.
- Implementation of Distributed Systems:
- Build robust distributed systems tailored for efficient ML training and seamless operational deployment.
- Feature Engineering Enhancement:
- Streamline and manage both online and offline feature stores, optimizing feature engineering processes for greater efficiency.
- AI-Driven System Development:
- Design and enhance cross-mode optimization systems to advance AI-driven approaches in transportation logistics.
- Real-Time ML Workflow Enhancement:
- Improve real-time machine learning workflows to support dynamic decision-making and automate core operational processes.
Required Qualifications
- Production Python Expertise:
- Advanced proficiency in Python, within a production environment impacting operations.
- Distributed Systems Expertise:
- Strong background in distributed computing, focusing scalability & high-performance infrastructure.
- Machine Learning / ML Ops / Data Engineering:
- Practical experience in implementing and deploying ML algorithms.
- Advanced SQL skills, particularly in OLTP systems, and expertise in caching mechanisms.
- Proficient in data engineering, distributed training, model monitoring, & experiment tracking.
Preferred Qualifications
- 3 to 5 years of industry experience in ML infrastructure, data engineering, or distributed systems.
- Strong understanding of ML Ops, high-scale data pipelines, and real-time data systems.
- Experience in logistics, transportation, or freight industries is a plus.
- Previous roles at major tech or logistics companies like Uber Freight, Lyft, Amazon, Walmart Global Tech, or Convoy.
The Perks
- Competitive Base Salary + Cash Bonus Structure
- Annual Company Bonus + Long Term Incentive Plan
- 401k with Matching
- Hybrid Work Schedule
- Comprehensive Health Coverage
- Hyper-Stable, publicly traded Enterprise
- Employee Stock Purchase Program (15% discount to market value)
- Collaborative, Tech-Forward office environment in Hayes Valley
Compensation Range: The annual base salary range for this position is $162,000 - $216,000*
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
- 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:
- 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.
- Creative, fast-paced environment to solve impactful problems in Supply Chain:
- 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.
Tags: Architecture Data pipelines Distributed Systems Engineering Feature engineering Machine Learning ML infrastructure Pipelines Python React SQL
Perks/benefits: 401(k) matching Career development Competitive pay Equity / stock options Salary bonus Startup environment
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