Sr. Product Manager -Artificial Intelligence and Machine Learning

Overview

WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.

AMD together we advance_

Sr. Product Manager – AI Infrastructure Software

THE ROLE:

We are seeking an experienced Sr. Product Manager to lead our AI accelerator software products, with a focus on AI clusters and Kubernetes integration. The ideal candidate will bridge the gap between technical capabilities and market needs in the rapidly evolving AI infrastructure space.

 

KEY RESPONSIBILITIES:
• Define product strategy and roadmap for AI cluster management and Kubernetes-based AI deployment solutions.
• Gather and prioritize product requirements from customers, market research, and internal stakeholders.
• Work closely with engineering teams to deliver high-quality software products.
• Analyze market trends and competitor offerings in AI infrastructure.
• Create and maintain product documentation, including user stories and specifications.
• Collaborate with sales and marketing to position and promote products effectively.
• Integrate expertise in systems architecture, networking, and software engineering to develop comprehensive, ready-to-deploy data center solutions.

PREFERRED EXPERIENCE:
• Proven years of experience in product management or a comparable technical role.
• Demonstrated track record of successfully delivering technical products from initial concept to market launch, with at least several years of hands-on experience in this capacity.
• Strong understanding of AI/ML workloads, distributed computing, and container orchestration.
• Proficiency in MLOps and LLMOps ecosystems, coupled with a proven track record of developing integrations for widely-used enterprise platforms.
• Excellent communication and stakeholder management skills.
• Experience with AI accelerator hardware (GPUs, TPUs, etc.)
• Knowledge of AI/ML frameworks and development workflows.
• Background in high-performance computing or data center infrastructure.

ACADEMIC CREDENTIALS:
• Bachelor’s Degree in Computer Science, Engineering, or related field; MBA is a plus.

 

LOCATION:
• Santa Clara, California, or Austin, Texas Preferred.

At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

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.

Company:

AMD

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Clustering, Industry, Machine Learning, NLP, United States