Hybrid opportunity at
ZooxStaff Software Engineer, HPC
Zoox seeks a Staff Software Engineer to shape, grow, and manage specialized High-Performance Computing infrastructure. In this position, the professional will modernize the HPC platform utilizing…
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About This Role
Zoox seeks a Staff Software Engineer to shape, grow, and manage specialized High-Performance Computing infrastructure. In this position, the professional will modernize the HPC platform utilizing tools like Ray.io, SLURM, and Kubernetes to support growing compute, storage, and scheduling needs. These systems serve as the foundation for software development across data engineering, simulation, and AI model training for autonomous vehicles. The role offers autonomy to shape technical and organizational strategy…
Job Description
Zoox seeks a Staff Software Engineer to shape, grow, and manage specialized High-Performance Computing infrastructure. In this position, the professional will modernize the HPC platform utilizing tools like Ray.io, SLURM, and Kubernetes to support growing compute, storage, and scheduling needs. These systems serve as the foundation for software development across data engineering, simulation, and AI model training for autonomous vehicles. The role offers autonomy to shape technical and organizational strategy while collaborating with various engineering teams.
This opportunity is well-suited for an experienced distributed systems specialist who enjoys autonomy, cross-functional collaboration, and building platforms that boost engineering productivity. Zoox focuses on creating an independent, ground-up autonomous vehicle fleet and mobility ecosystem designed for urban areas. The organization values diverse perspectives and encourages candidates who bring varied backgrounds to apply, even if they do not meet every single listed expectation.
Responsibilities
- Design and build foundational services and abstractions for distributed compute systems supporting hundreds of thousands of concurrent jobs
- Partner with customer and infrastructure teams to create a multi-year software engineering roadmap for the HPC platform
- Direct multi-quarter, cross-team initiatives that improve the broader organization
- Build production-grade APIs, SDKs, and tooling to help engineers run large-scale distributed tasks
- Refine job scheduling algorithms and auto-scaling policies to enhance reliability and resource access
- Formulate multi-region orchestration strategies focused on data locality, performance, and dependability
- Diagnose and fix systemic reliability and performance challenges through profiling and collaboration
- Assess emerging technologies to enhance computational and storage capacities
- Build capacity planning tools and forecasting models to address expanding compute demands
- Coach junior engineers and support their career growth
Requirements
- Experience designing and operating large-scale distributed systems in production environments
- Experience working with Ray.io, particularly Ray Core and Ray Data, or similar technologies
- Experience utilizing Kubernetes for heterogeneous workloads
- Experience with cloud infrastructure on AWS or comparable providers
- Proven track record of delivering and managing reliable, highly available scalable infrastructure
- Demonstrated ability to prioritize tasks and build cross-functional consensus on technical tradeoffs
- Proficiency in Python
Qualifications
- Exposure to machine learning workloads including training, inference, and data generation
- Experience running Kubernetes or SLURM at scale across more than 10,000 nodes
- Experience with the SLURM workload manager and advanced scheduling policies
- Background in algorithmic optimization or operations research
- Experience constructing developer tools and platforms for large engineering companies
Core Skills
Frequently Asked Questions
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The posting indicates that the position has a hybrid remote status.
What is the employment type for this role?
The position is full-time.
What is the salary for this Staff Software Engineer role?
The salary is not specified in the job posting.
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