Job Summary:
Fluidstack is a company that builds the compute, data centers, and power to fuel artificial superintelligence. They are seeking a Product Manager to lead New Product Introduction for GPU infrastructure, collaborating with various teams to bring new GPU generations to market and ensure competitive offerings for AI workloads.
Responsibilities:
• Own the NPI roadmap for GPU SKUs, including evaluation criteria, qualification timelines, and go-to-market strategy for new hardware generations
• Partner with datacenter teams to define requirements for power delivery (HVDC/LVDC), cooling (liquid vs. air), rack architecture, and physical infrastructure needed for next-gen GPUs
• Work with infrastructure engineers to validate hardware performance across key dimensions: training throughput (MFU), inference latency (TTFT, TBT), memory bandwidth, interconnect topology (NVLink, InfiniBand)
• Drive vendor engagement with NVIDIA, AMD, and emerging XPU providers—conducting technical deep dives, negotiating supply agreements, and managing early access programs
• Define product specifications for system configurations: single-GPU instances, multi-GPU nodes, full rack deployments, and megacluster topologies
• Analyze customer workload profiles to determine optimal GPU mix: H100 for large model training, L40S for inference, B200 for frontier research, MI300X for cost-sensitive workloads
• Build business cases for new SKU introductions, including CapEx requirements, depreciation models, utilization forecasts, and competitive pricing analysis
• Create technical documentation and benchmarking reports that help customers select the right GPU for their use case
• Monitor GPU availability, supply chain constraints, and allocation strategies to ensure Fluidstack can meet customer demand while maintaining healthy margins
• Collaborate with networking teams to ensure interconnect fabric (RoCE, InfiniBand) scales with GPU performance and supports distributed training patterns
Qualifications:
Required:
• 5+ years product management experience with at least 3 years focused on infrastructure, hardware platforms, or cloud compute services
• Strong technical background in GPU architecture, accelerator performance characteristics, and AI workload requirements
• Experience managing NPI processes from evaluation through production deployment—including vendor relationships, qualification testing, and rollout planning
• Deep understanding of datacenter infrastructure: power distribution, thermal management, rack design, and high-density deployment constraints
• Track record of making build vs. buy decisions on hardware platforms based on TCO analysis, competitive positioning, and customer demand signals
• Familiarity with GPU performance metrics (TFLOPS, HBM bandwidth, TDP, MFU) and how they translate to real-world training and inference performance
• Ability to work with engineering teams to debug hardware issues, analyze telemetry data, and identify root causes of performance degradation
• Experience conducting competitive analysis of cloud GPU offerings from AWS, GCP, Azure, CoreWeave, Lambda Labs, and other specialized providers
• Comfortable navigating supply chain complexity, allocation negotiations, and procurement timelines with hardware vendors
Preferred:
• Experience with networking topologies (fat tree, rail-optimized), storage systems (NVMe, Ceph), or HPC infrastructure design
Company:
Fluidstack accelerates the world’s most ambitious AI projects by removing the bottlenecks to compute. Founded in 2017, the company is headquartered in London, GBR, with a team of 51-200 employees. The company is currently Growth Stage.