Technical Consultant

Position Overview

We are seeking a Technical Consultant to join our team working on ClusterMAX™, the industry standard GPU Cloud rating system. We are hiring at all experience levels with competitive compensation.

Responsibilities

• Lead ClusterMAX™ consulting engagements, including technical due diligence projects related to neoclouds, AI accelerators, AI infrastructure, AI labs, and adjacent ecosystems.

• Translate ClusterMAX™ benchmarking and testing insights into actionable recommendations and investment decisions for clients.

• Contribute to the development of next-generation benchmarking methodologies, TCO analysis frameworks, and future ClusterMAX™ research initiatives.

• Collaborate with executives, engineers, and technical teams across major neocloud providers, including Amazon Web Services, Microsoft Azure, Google Cloud, Oracle, CoreWeave, Nebius, Crusoe, Lambda, and others.

• Build and maintain relationships with AI accelerator manufacturers, OEMs, and ecosystem partners, including NVIDIA, AMD, Intel, Google, Amazon, Cerebras, Groq, Dell Technologies, Hewlett Packard Enterprise, and others.

• Strengthen relationships with AI labs, investors, startups, and technical communities to better understand industry requirements and operational challenges.

• Author detailed technical research reports evaluating architecture design, benchmark performance, reliability, scalability, and operational usability of neocloud and AI infrastructure providers.

• Stay informed on emerging trends and technologies through participation in major industry conferences such as NeurIPS, MLSys, NVIDIA GTC, OCP, SC, and Hot Chips.

Requirements

• Strong understanding of ML frameworks such as PyTorch and JAX.

• Familiarity with GPU and TPU cluster environments running orchestration platforms such as Kubernetes or Slurm.

• Understanding of distributed storage technologies including Weka, VAST, Lustre, and S3-based storage systems.

• Knowledge of high-performance networking technologies such as InfiniBand and RoCEv2.

• Understanding of ML systems benchmarking and performance testing tools, including GEMMs, nccl-tests, vLLM, sglang, fio, TorchTitan, Megatron, and related frameworks.

• Experience working at a hyperscaler, neocloud provider, server OEM, AI accelerator company, or large-scale AI infrastructure environment is preferred.

• Ability to work proactively and independently within a globally distributed team environment.

• Strong analytical, technical communication, and problem-solving capabilities.

Growth Areas

• Develop deep expertise in AI infrastructure, neocloud ecosystems, accelerators, and large-scale ML system benchmarking.

• Gain exposure to technical due diligence and investment decision-making processes across frontier AI and semiconductor markets.

• Build relationships with leading hyperscalers, AI labs, infrastructure startups, accelerator vendors, and institutional investors.

• Contribute to industry-recognized benchmarking methodologies and technical research publications.

• Expand technical knowledge across distributed systems, networking, storage, AI infrastructure, and performance optimization.

• Work directly with globally recognized companies shaping the future of AI compute and infrastructure.

• Increase visibility within the AI and semiconductor ecosystem through conferences, technical collaborations, and published research.