The company

Outrider, the pioneer in autonomous yard operations for logistics hubs, helps large enterprises improve safety, increase efficiency, and optimize their workforce. The only company exclusively focused on automating all aspects of yard operations, Outrider eliminates manual tasks that are hazardous and repetitive. Outrider’s mission is to drive the rapid adoption of sustainable freight transportation by deploying zero-emission systems. Outrider is a private company backed by NEA, 8VC, and other top-tier investors.

The role

We’re looking for a machine learning engineer to set up our data infrastructure for our entire system off robot. This individual will own and deliver on everything from data ingestion to machine learning data management with a large degree of autonomy.

This position plays an essential role in helping deliver a reliable, profitable, performant, safety-critical system -- it offers a very talented software engineer the chance to help develop a market-defining enterprise product that combines autonomous vehicle technology with a software-as-a-service (SaaS) business model.

The ideal candidate will embrace our goal to drive zero-emission, self-driving vehicle adoption, and help us realize our potential to define, build, and lead a new, category of robotic automation for the enterprise.

Duties and responsibilities

• Drive the full software development process for the underlying infrastructure and plumbing of our machine learning system
• Stay informed about cutting edge best practices and implementation
• Own a mission critical piece of our system to deliver autonomous systems into production

Required qualifications

• Bachelor's degree in computer science, machine learning, or related field
• 1-3+ years of experience building machine learning infrastructure
• Production experience with any of the following: Hadoop, Spark, Apache Airflow, Presto, Docker, or Kubernetes
• Experience developing services deployed within cloud or data center environments
• Experience developing batch or stream processing workflows

Ideal qualifications

• Masters degree in computer science or related field
• 3-5+ years of experience building machine learning infrastructure