Build Kubernetes training infrastructure at Waabi, using Python and AWS to support Physical AI for autonomous trucks and robotaxis.
This senior engineering role develops platforms used by ML researchers and engineers. You will shape APIs, CLIs, experiment workflows, and reliable production systems. The work spans distributed PyTorch training, GPU scheduling, data pipelines, and model delivery.
Key Responsibilities
Build Kubernetes infrastructure for distributed GPU training workloads
Design developer-facing CLIs, SDKs, templates, and workflows
Strengthen dataset versioning, sharding, and artifact loading
Implement observability for utilization, failures, queues, and costs
Ship CI/CD for models alongside autonomy and simulation
Requirements
Five or more years in software or infrastructure engineering
Excellent Python and experience designing usable APIs and CLIs
Practical AWS, IAM, GPU, networking, and infrastructure-as-code expertise
Distributed PyTorch training with experiment tracking and model registries
Fluency with containers, CI/CD, and up-to-date build systems
Use Python, AWS, Kubernetes, and distributed training expertise to advance Waabi's autonomous transportation infrastructure.