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Why this grade This listing scored 27/100, which is an F. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Freshness 4 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
-10 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
This listing does not state a salary
$135k – $195k
That is the middle half of what comparable roles paid on this board over the last 90 days — 44 listings that did publish a figure, median $168k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
Senior Product Manager – GPU Products & AI Infrastructure
Why This Opportunity?
This is an opportunity to shape the future of AI and accelerated computing in the cloud. You will play a pivotal role in defining the GPU products, clusters, and services designed to support demanding AI, HPC, graphics, and enterprise workloads at a global scale. Working at the intersection of product strategy, AI infrastructure, cloud computing, and advanced GPU technology, you will partner with engineering and industry technology leaders to bring innovative, foundational products to market
What We're Looking For (Required & Elite Qualifications)
To land this role, you must possess a rare blend of deep hardware-level intelligence and hyperscale product management acumen. We are filtering for candidates who meet the following high-bar criteria:
- Professional Experience:12+ years of relevant product management, technology, or engineering experience in massive-scale cloud or hardware ecosystems.
- Target Domain Expertise:Direct, hands-on experience managing GPU cloud infrastructure or accelerated computing products.
- AI & Accelerated Computing:Strong technical understanding of GPU architectures (e.g., NVIDIA, AMD), CUDA, and accelerated computing platforms.
- Cluster Orchestration:Deep experience with AI/HPC workloads and GPU cluster orchestration(including resource management, fabric, interconnects like NVLink/InfiniBand, and large-scale GPU deployments).
- Financial Mastery:Proven capability in developing complex business and financial frameworks for infrastructure, including pricing, TCO, or profitability models.
- Advanced Infrastructure Literacy:Deep knowledge of AI workload patterns, enterprise security requirements, and hardware-level APIs related to GPU infrastructure.
- Execution & Leadership:A strong customer-first mindset with a hyper-focus on automation, usability, and low-friction integration for data scientists. Exceptional ability to gain buy-in from highly technical engineering teams.
- Education: Bachelor's degree in Computer Science, Engineering, or equivalent deeply technical practical experience
What You'll Do
- GPU Strategy & Vision:Define the product strategy, vision, and roadmap for next-generation GPU instances, high-performance clusters, and cloud services.
- Workload Architecture: Translate complex AI, HPC, graphics, and accelerated-computing workloads into rigid product specifications, performance requirements, and technical architectures.
- Lifecycle & Investment:Guide the evolution of GPU infrastructure and make data-driven decisions around platform investments, resource management, and lifecycle management from concept to end-of-life.
- Cloud Economics:Develop advanced business cases, financial models, pricing strategies, profitability analyses, and TCO models to aggressively support product investments.
- Ecosystem Partnership:Partner directly with primary GPU technology and ecosystem providers to align roadmaps, integrations, and bleeding-edge technical requirements.
- Go-To-Market Execution:Develop and execute comprehensive go-to-market strategies, including product messaging, positioning, launch plans, and customer engagement alongside sales and solutions engineering.
- User Advocacy:Represent the direct needs of enterprise customers, engineers, and data scientists by identifying opportunities to improve automation, orchestration, monitoring, and usability.
Originally posted on Himalayas
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Where this listing came from
- 24 Aug 2026 Himalayas first sighting
Seen on 1 board over 0 days.