AMD

2 weeks ago

AI/ML Platform Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 9 hours agoStatus: Live

Job Summary

Build and operate the platform layer for AI-for-engineering workflows, enabling agent execution, distributed training and inference, experiment tracking, benchmark automation, and artifact management. Develop reliable infrastructure for large-scale GPU cluster workloads, including scheduling, observability, and reproducible evaluation. Partner with ML systems research and applied AI engineers to productionize research workflows and make Blueprint harnesses reusable across kernel, RTL, verification, and performance pipelines.

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Build and operate the shared AI platform for agentic engineering workflows, including job submission, scheduling, orchestration, retries, logging, artifact storage, and experiment tracking.
•Develop reliable infrastructure for distributed training, distributed inference, batch evaluation, and large-scale agent rollout across GPU clusters.
•Build platform services for benchmark execution, correctness checking, profiling, regression tracking, and reproducible evaluation.
•Maintain artifact systems for generated kernels, RTL edits, traces/logs, profiler outputs, simulator outputs, benchmark results, and formal verification artifacts.
•Support integrations with compilers, ROCm/HIP tooling, profilers, simulators, EDA tools, vLLM, SGLang, and internal engineering systems, and improve GPU cluster utilization and observability.

Pay and Benefits

Salary: USD 178,500 - 306,000 annually

Key Requirements

•Strong programming skills in Python and one or more systems languages such as C++, Go, or Rust.
•Experience building ML platforms, AI infrastructure, distributed systems, workflow orchestration, experiment platforms, GPU cluster infrastructure, or developer platforms.
•Strong understanding of job scheduling, distributed workloads, logging, monitoring, reliability, storage systems, and production operations.
•Experience with Kubernetes, Ray, Slurm, workflow engines, containerization, CI/CD, data pipelines, or large-scale compute orchestration.
•Ability to build reliable services, APIs, dashboards, and developer tools used by researchers and engineers.

Experience:AI/MLDistributed systemsML platformsGPU infrastructureExperiment tracking

Education:Bachelor's

Skills:ReproducibilityObservabilityDebuggingCollaborationDeveloper experience

Languages:English

Tech Stack:PythonC++GoRustROCm/HIPCUDATritonVLLMSGLangPyTorchJAXKubernetesRaySlurmMLflowWeights & BiasesCI/CDContainerizationAPIsDashboards

Company Brief

AMD

Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1969

Glassdoor: 3.9

Website LinkedIn

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AMD