Software Engineer, ML Performance Optimization

Zoox

Foster City, US

Who this role is best for

Best suited to mid-level software engineers with ML performance optimization experience working in autonomous vehicle technology.

Best fit for

Engineers who thrive at the intersection of ML frameworks and hardware efficiency.
— “deep learning frameworks, and inference systems”
Those who want to push boundaries in ML practice.
— “significantly push the boundaries of how ML is practiced”

Things to consider

Role involves leadership responsibilities over a team.
— “lead a team of strong software engineers”
Must collaborate with multiple specialized ML teams.
— “work across all ML teams within Zoox”

How to stand out

Demonstrate experience optimizing ML training/inference pipelines.
— “make our Training and Inference platform”
Highlight leadership in performance-critical ML systems.
— “lead our ML Performance Optimization initiatives”

Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · TeamLevel · Mid Level

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

lead ML performance optimization initiatives
work across all ML teams
significantly push the boundaries of how ML is practiced

Typical background

experience in machine learningbackground in software engineering

Skills & requirements

Required

Machine LearningPerformance OptimizationDeep Learning FrameworksInference Systems

Preferred

Autonomous DrivingComputer Vision

About the role

Original posting from Zoox via Lever

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible.
The Opportunity
Are you excited to lead our ML Performance Optimization initiatives and make our Training and Inference platform that enables autonomous driving as fast and efficient as possible? You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and Advanced Hardware Engineering group and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.
We build and operate the base layer of ML tools, deep learning frameworks, and inference systems used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and act as a force multiplier for our internal customers. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here.

Source: Zoox careers (Lever)