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Software Engineer - Infrastructure, Machine Learning

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San Francisco (CA)

Hybrid

USD 162,000 - 216,000

Full time

3 days ago
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Job summary

Join a forward-thinking company at the forefront of logistics technology, where you will leverage your software engineering skills to optimize machine learning infrastructure. In this hybrid role, you'll tackle complex challenges in distributed systems, enhancing the efficiency of supply chains. With a competitive salary and a dynamic work environment, you will have the opportunity to make a significant impact from day one. Collaborate with a talented team to design innovative solutions that address real-world problems in transportation logistics, all while enjoying the stability of a well-established industry leader.

Benefits

Competitive Base Salary + Cash Bonus Structure
Annual Company Bonus + Long Term Incentive Plan
401k with Matching
Hybrid Work Schedule
Comprehensive Health Coverage
Employee Stock Purchase Program (15% discount)
Collaborative, Tech-Forward Office Environment

Qualifications

  • 3-5 years of industry experience in ML infrastructure or distributed systems.
  • Strong understanding of ML Ops and high-scale data pipelines.

Responsibilities

  • Optimize ML architecture to enhance system performance.
  • Build robust distributed systems for efficient ML training.

Skills

Python
Distributed Systems
Machine Learning
Data Engineering
SQL

Education

Bachelor's Degree in Computer Science or related field

Tools

OLTP Systems
Caching Mechanisms

Job description

Job DescriptionJob DescriptionWho 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

Basic Job Details

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.

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.
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