Note: The job is a remote job and is open to candidates in USA. AMD is seeking a Senior Product Manager to drive strategy and execution for ROCm, AMD’s open-source GPU software stack, with a specific focus on large-scale model inference on AMD Instinct™ and Radeon™ hardware. This role involves engaging with the open-source community, influencing engineering roadmaps, and connecting customer needs with the open-source ecosystem.
Responsibilities
- Own the product roadmap for ROCm’s inference software capabilities, including integrations with key frameworks like PyTorch and JAX, serving runtimes like vLLM and SGLang, and the libraries and profiling tools that make inference workloads perform well on AMD hardware
- Define and communicate a coherent strategy for how AMD software enables production inference workloads, covering the full range from single-GPU to rack-scale deployments, with a focus on developer experience, performance portability, and competitive standing
- Identify when emerging OSS model architectures, serving runtimes, or inference techniques require an AMD software response and drive those requirements into the roadmap
- Bring a strategic lens to inference by continuously evaluating the latest research, technology trends, and evolving deployment needs, ensuring the organization stays ahead of future inference requirements and translates market signals into actionable product strategy
- Serve as AMD’s active presence in the open-source AI/ML community: monitor GitHub repositories, Discord servers, developer blogs, and academic papers to track emerging trends, pain points, and opportunities
- Own and communicate AMD’s open-source software roadmap, publishing updates across key community projects to build awareness, solicit feedback from model developers and researchers, and signal AMD’s long-term direction to the open-source ecosystem
- Build and maintain relationships with key OSS maintainers, foundation working groups, and community contributors whose work shapes how AMD hardware is perceived and adopted
- Represent AMD at major conferences such as SC, PyTorch Conference, and MLSys; write and review technical blog posts and community announcements on the AMD ROCm blog
- Partner with engineering leads across inference libraries, kernel, runtime, and serving integration teams to translate developer and customer needs into prioritized engineering work
- Drive release planning across rapid release cadences with a CI/CD-first mindset and strong attention to compatibility, regression, and ecosystem readiness
- Provide software-informed feedback to hardware teams on future GPU architecture decisions, particularly where features relevant to inference workloads affect serving performance at scale
- Balance the signal from large customers, who may need specific optimizations or bespoke integrations, against the needs of the broader open-source community, who value standards, portability, and low friction
- Collaborate with ecosystem partners such as Hugging Face, Red Hat, and cloud providers on joint integrations and AMD-supported software solutions
Skills
- Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field
- Proven years of product management experience in a software-focused role, ideally developer tools, GPU computing, or AI/ML infrastructure
- Deep familiarity with at least one of PyTorch, JAX, or Triton: how they are structured, how they dispatch work to hardware backends, and what the end-to-end developer experience looks like
- Practical understanding of LLM inference, including attention mechanisms, KV cache design, quantization strategies such, continuous batching, speculative decoding, and parallel serving across multiple GPUs
- Hands-on familiarity with GPU programming at some level, whether HIP, CUDA, or Triton kernels, with the ability to read kernel-level code and benchmark output even if not writing it day to day
- Strong written communication skills across technical documentation, roadmap narratives, community blog posts, and executive-facing strategy documents
- Prior experience at a GPU vendor, cloud provider AI infrastructure team, or frontier AI lab
- Experience contributing to or managing products in an open-source context: GitHub workflows, community governance, and OSS release management
- Contributions in code, issues, or documentation to major open-source inference projects such as vLLM, SGLang, Triton, or PyTorch
- Familiarity with AMD's hardware portfolio: Instinct MI-series for data center compute and Radeon for workstation and consumer GPU compute
Benefits
- Benefits offered are described: [AMD benefits at a glance](https://www.amd.com/en/corporate/careers/benefits.html).
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