2 months ago
San Jose, CA, USASenior
Responsibilities
- Design and develop distributed control-plane services, APIs, schedulers, inference gateways, and command-line tools.
- Build reliable orchestration for GPU training, inference, custom jobs, and interactive development workloads.
- Develop scalable scheduling and admission-control features including priority, fairness, topology-aware placement, quotas, backfilling, and multi-node coordination.
- Implement reconciliation, lifecycle management, retries, idempotency, and recovery across PostgreSQL and external execution systems.
- Integrate Fleet Manager with Kubernetes, Kueue, JobSet, container runtimes, storage systems, and observability platforms.
- Develop GPU health, diagnostics, quarantine, remediation, secure multi-tenant infrastructure, and reliable AI inference services.
- Maintain stable APIs, data models, compatibility contracts, and operational procedures.
- Diagnose failures across distributed services, Kubernetes, networking, storage, GPU runtimes, drivers, and hardware.
- Develop automated unit, integration, failure-injection, and production-readiness tests.
- Provide technical leadership through design reviews, code reviews, mentoring, and cross-functional problem solving.
Requirements
- Strong systems-software development experience in Rust, C++, Go, or a comparable language, with production Rust highly desirable.
- Experience designing and operating distributed systems, control planes, schedulers, or cloud infrastructure.
- Strong understanding of concurrency, asynchronous programming, state machines, and failure recovery.
- Experience building services using REST, streaming, WebSocket, or gRPC APIs.
- Experience with Kubernetes internals, controllers, operators, scheduling, resource management, or custom resources.
- Experience with PostgreSQL-backed services, schema evolution, transactions, leader election, and optimistic concurrency.
- Experience developing command-line tools and stable, user-focused APIs.
- Understanding of container security, multi-tenant isolation, authentication, authorization, and secrets management.
- Experience with production observability, source control, continuous integration, automated testing, profiling, and debugging tools.
- Ability to lead technically challenging projects and collaborate across organizational boundaries.
- A bachelor’s or master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent practical experience.
- Beneficial experience includes AMD GPU architecture, ROCm, HIP, amd-smi, RCCL, GPU device plugins, distributed AI training, vLLM, SGLang, PyTorch, GPU infrastructure, Kubernetes networking and storage, inference APIs, shared storage, and production security.
Benefits
- AMD benefits are referenced through the company’s benefits-at-a-glance information.
Tech Stack
About AMD
AMD designs and sells CPUs, GPUs, and adaptive/embedded computing products for PCs, data centers, gaming, and edge devices. Its portfolio includes Ryzen and EPYC processors, Radeon and Instinct graphics, and adaptive SoCs from its Xilinx acquisition, sold to OEMs, cloud providers, and device makers. Founded in 1969 and headquartered in Santa Clara, it is a public company on NASDAQ and supplies semi-custom chips for major game consoles.