ML Platform Engineer: Scalable Kubernetes & Ray

Avride Inc.; Austin (TX); On-site; USD 130,000 - 175,000; Full time

Job summary

Avride Inc. in Austin, Texas, is seeking an ML Platform Engineer to own core ML stack components such as workflow orchestration, distributed execution, and resource governance.

You will help ML teams run experiments and train models at scale on Kubernetes, with a focus on reliability and developer experience. You will build abstractions and services that enable scalable, cost-efficient, and fast training workloads, collaborating with ML teams to debug issues and drive platform improvements.

Qualifications

• Proficiency in Python or Go; C++ is a plus.
• Track record of designing and building scalable, maintainable systems and services.
• Experience operating production services end-to-end: APIs, reliability practices, observability.
• Deep knowledge of Kubernetes: scheduling, resource management, controllers, and pod lifecycle under pressure.
• Solid Linux and systems debugging skills: performance investigation, networking, storage/IO.
• Ability to troubleshoot complex production issues across logs, metrics, and traces and drive them to resolution.

Responsibilities

• Build and scale ML compute platform on Kubernetes, using Argo Workflows for training, evaluation, and data processing orchestration.
• Design and implement core platform capabilities, including a Ray-based internal SDK for distributed execution, and multi-tenant resource governance.
• Improve end-to-end training throughput and platform efficiency by optimizing data access patterns, caching, and removing bottlenecks in storage, network, and resource contention.
• Work directly with ML teams to debug complex workload issues, drive root-cause analysis, and turn recurring problems into platform-level fixes.
• Evaluate, integrate and extend open-source tooling (Argo Workflows, Ray, Kubernetes ecosystem) to meet evolving platform needs.

Skills

Python

Go

C++

Tools

Kubernetes

Argo Workflows

Ray

MLflow

Job description

Avride Inc. in Austin, Texas, is seeking an ML Platform Engineer to own core ML stack components such as workflow orchestration, distributed execution, and resource governance.

You will help ML teams run experiments and train models at scale on Kubernetes, with a focus on reliability and developer experience. You will build abstractions and services that enable scalable, cost-efficient, and fast training workloads, collaborating with ML teams to debug issues and drive platform improvements.