Description
WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE ROLE:
This role sits within AMD's Enterprise AI product organization, working at the intersection of AI software, infrastructure, and platform strategy. The team is responsible for shaping and delivering enterprise-grade AI platforms that span ROCm infrastructure, Kubernetes orchestration, GPU virtualization, AI frameworks, and performance optimization.
In this role, you will work directly with senior product leadership and collaborate closely with cross-functional engineering teams to translate complex technical capabilities into cohesive, production-ready enterprise AI solutions. You will gain exposure to the full product lifecycle — from strategy and roadmap definition to execution, launch, and post-release iteration — while learning how large-scale AI platforms are built and operated in real enterprise environments.
This is a highly collaborative, fast-moving environment where curiosity, systems thinking, and a willingness to learn are valued. The role offers hands-on experience across hardware-aware software stacks, modern cloud-native platforms, and enterprise AI use cases, with opportunities to grow technical depth and product leadership skills.
THE PERSON:
The ideal candidate is intellectually curious, technically grounded, and motivated to learn quickly in complex problem spaces. You enjoy working across disciplines, asking good questions, and turning ambiguity into clarity. You are comfortable engaging with engineers and stakeholders at different levels, and you take ownership of outcomes even when the path forward is not fully defined.
You are detail-oriented but able to think at a systems level, balancing technical depth with product perspective. You communicate clearly, listen actively, and value collaboration. You are excited by the challenge of building enterprise AI platforms that move beyond experimentation into real-world production use.
KEY RESPONSIBILITIES:
Partner with Enterprise AI product leadership to support product strategy, roadmap development, and execution across AI/ML platforms and services.
Work closely with cross-functional engineering teams (AI frameworks and libraries, Kubernetes and orchestration, GPU virtualization, model performance, and ROCm infrastructure/software) to translate strategic objectives into clear product requirements.
Contribute to the end-to-end product lifecycle for assigned features or components, including requirements definition, prioritization, release readiness, and post-launch evaluation.
Collaborate with internal teams and partners to align technical dependencies, APIs, and ecosystem integrations.
Engage with internal stakeholders and customers to gather feedback, validate use cases, and inform iterative product improvements.
Support go-to-market and enablement efforts through the development of technical collateral, demos, and internal documentation.
Track progress, communicate status, and surface risks or trade-offs to cross-functional teams and leadership.
What success looks like over time:
First 3 months: Build foundational understanding of the enterprise AI stack, product roadmap, and cross-functional workflows; contribute to requirements and planning discussions.
6 months: Independently own defined product areas or features, drive alignment across teams, and contribute meaningfully to roadmap execution.
12 months: Operate as a trusted product partner across engineering teams, influencing product direction and helping deliver enterprise-ready AI capabilities at scale.
PREFERRED EXPERIENCE:
Experience or strong exposure to machine learning systems, AI model lifecycles, or AI/ML frameworks such as PyTorch, TensorFlow, ONNX, or similar.
Familiarity with cloud-native technologies, such as Kubernetes, containerized workloads, or distributed systems.
Exposure to GPU compute stacks, performance optimization, virtualization concepts, or infrastructure-aware software is a plus.
Experience translating technical concepts into product requirements, documentation, or stakeholder communications.
Participation in internships, research projects, open-source contributions, or industry projects related to software, AI/ML, or infrastructure.
ACADEMIC CREDENTIALS:
Bachelor's degree preferred in Computer Science, Computer Engineering, Software Engineering, or a related technical field.
Coursework or academic projects in machine learning, distributed systems, systems programming, or scalable software architectures preferred.
ACADEMIC CREDENTIALS:
- Santa Clara, CA
This role is not eligible for visa sponsorship.
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Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
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