Senior Software Engineer - HPC Cost Optimization & Efficiency

zoox

4100

Foster City, CA, USA

Posted on: 2026-01-06

Category: emobility

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Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

About the company:

Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.

Zoox is looking for an experienced Software Engineer to drive cost optimization and efficiency improvements across our custom High-Performance Computing infrastructure managing annual compute spend. As Zoox scales its autonomous vehicle development, intelligent resource management and cost efficiency have become critical to our success. You will modernize our HPC platform—built on industry-leading technologies like Ray.io, SLURM, and Kubernetes—with a focus on maximizing utilization, eliminating waste, and reducing cloud costs while maintaining world-class developer velocity. These HPC services form the backbone of development workflows across all Zoox software teams, from data engineering to training our AI models in Perception, Planner, Prediction, to Simulation, and more. You will have a direct impact on Zoox's bottom line through measurable cost reductions and efficiency gains.

The position comes with a high degree of independence and the opportunity to define Zoox's compute economics strategy, both technically and organizationally. You will work closely with stakeholders in Autonomy and Software teams to balance performance requirements with cost constraints, incorporating FinOps best practices and the latest cost optimization techniques.

About Zoox

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

In this role, you will:

Design and implement cost optimization strategies across distributed compute infrastructure, targeting millions in annual savings

Build cost visibility, attribution, and chargeback systems to drive accountability and informed decision-making

Optimize job scheduling algorithms and auto-scaling policies to maximize resource utilization and minimize idle capacity

Design multi-region orchestration strategies that optimize for data locality, cost and performance

Identify and eliminate inefficient workload patterns through profiling, analysis, and developer education by coordinating with workload owners across multiple teams

Evaluate new technologies and paradigms that reduce cost while meeting Zoox's computational and storage needs

Develop cost forecasting models and budget management tools for capacity planning

Implement cloud cost optimization strategies including spot instances, reserved capacity, and right-sizing

Create production-grade APIs, SDKs, and tools that make cost-efficient patterns the default developer experience

Qualifications

Experience optimizing large-scale distributed systems for cost and efficiency

Experience with Ray.io, particularly Ray Core and Ray Data

Experience with Kubernetes, particularly for heterogeneous workloads and cost optimization

Experience with cloud cost management on AWS (Cost Explorer) or similar providers

Track record of achieving measurable cost reductions in production infrastructure

Demonstrated ability to prioritize development work and build cross-functional consensus around cost/performance tradeoffsProficiency with Python

Bonus Qualifications

Understanding of FinOps principles and practices

Experience building cost attribution, chargeback, or showback systems

Exposure to machine learning workloads (training, inference, data generation) from a cost optimization perspective

Experience with Kubernetes or SLURM at scale (>10k+ nodes)

Experience with SLURM workload manager and advanced scheduling policies

Background in algorithmic optimization or operations research

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