AI/GPU Infrastructure Specialist Required

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@ashinnd84

With over a decade of hands-on experience in transforming complex business ideas into robust digital solutions, I lead a team of 35+ highly skilled developers across multiple sectors. Our work has often intersected with AI and machine learning technologies, making us well-equipped to undertake the AI/GPU Infrastructure Specialist role you seek. Our deep understanding of Python, Java, and AI concepts puts us in prime position to assist with GPU server configurations, cooling architectures, and infrastructure requirements for your demanding AI workloads. Additionally, our command over DevOps tools such as Docker and Kubernetes will enable us to provide technical evaluations and guidance promptly and efficiently. We have worked extensively on GPU platforms, data center environments, and NVIDIA GPU technology, which aligns perfectly with your expectations from the ideal candidate. Our proficiency with liquid cooling solutions like direct-to-chip liquid cooling or immersion cooling enhances our utility in this project and can help you achieve advanced thermal management required for your AI/GPU systems. Together with our sound knowledge of high-end GPU architecture and enterprise data center infrastructure management, we believe our expertise is an ideal fit for this project's needs. Let's transform your AI infrastructure for optimal performance together!

@TechizeBuilder

Dear Client, I read "AI/GPU Infrastructure Specialist Required" carefully and understand you want clean, modern Figma designs that translate smoothly into a real product. My hands-on experience with Artificial Intelligence, AI (Artificial Intelligence) HW/SW aligns directly with what you need. I design in Figma with a focus on usability and visual polish — wireframes, high-fidelity mockups, prototypes and design systems — handed off dev-ready so nothing gets lost in build. A few quick questions to get us started: 1. Is this for a website, mobile app, or both? 2. Do you have existing branding (logo, colors, fonts), or should I help define it? 3. Do you need clickable prototypes, or static screens with a handoff-ready design system? Thanks & Regards, Deepak

@NEHABHAT92

As an AI/GPU Infrastructure Specialist, my team and I at Neha's tech company are your one-stop solution for all things related to high-performance computing systems and GPU architecture. We have a rich experience of over 9+ years in web and mobile development that comes handy when dealing with complex infrastructure requirements for AI workloads. Our expertise includes GPU hardware, server architecture, liquid cooling solutions like direct-to-chip or immersion cooling, precisely what you're looking for. Our diversified skill set which spans across Android, iOS, Java, PHP, HTML5/CSS/Responsive Design among others is beneficial in handling the wide array of complex tasks this project entails. Our extensive experience in developing E-commerce sites and CMS-based websites attests to our effectively costed projects and thoroughness when it comes to post-delivery support. Your project description emphasizes scaling up AI compute environments; needless to say, I assure you complete attention to detail in the design, deployment and maintenance of your AI/GPU clusters as well as your enterprise-grade data center infrastructure. In us, you have a reliable ally that takes care of the nitty-gritties so you divert your focus on innovation and core areas of your business. Give us this opportunity and we guarantee turning your digital ideas into reality! Let's get started on unravelling the potential of real-time artificial intelligence:

@anjalio22

I would appreciate the opportunity to support your AI/GPU infrastructure project. With experience in high-performance computing environments, AI hardware integration, and enterprise infrastructure planning, I can provide practical guidance on GPU server architecture, liquid cooling strategies, and scalable AI compute deployments. My expertise includes NVIDIA GPU platforms, GPU cluster design, Docker, Kubernetes, DevOps workflows, and AI/ML infrastructure optimization. I can assist with evaluating direct-to-chip liquid cooling, immersion cooling, thermal performance, power and rack planning, server configurations, and data center deployment considerations to ensure reliable, high-performance AI workloads. I focus on delivering technically sound recommendations backed by careful analysis, clear documentation, and professional communication throughout the project. My goal is to help you build an efficient, scalable, and future-ready AI infrastructure while meeting performance, reliability, and operational requirements. Give me one opportunity to handle your project. I assure you that I will complete the work with full dedication, accuracy, and professionalism while delivering high-quality results on time.

@qiangz0

As an experienced professional in the world of AI and machine learning, I am confident that my unique skill set aligns perfectly with your needs for this particular project. Spanning skills in online sales, data analysis, market research and industrial AI applications , my approach to complex challenges is rooted in using cutting-edge technology to drive efficiency, innovation and revenue growth. My expertise in using GPU hardware, server architecture and direct-to-chip liquid cooling can be directly employed to your AI/GPU infrastructure optimization needs. Also relevant to this project is my experience in optimizing digital marketing spend based on data analysis – a skill that can be hugely valuable when applied to deploying scalable AI compute environments in an efficient manner. These are all key components towards maximizing utility from AI clusters, which ultimately results in enhanced performance and productivity.

@mahmoud1911

Hello there, I hope you're doing well. I'm genuinely interested in supporting your project. I bring over 15 years of experience in IT, media production, and technical operations, specializing in: GPU & AI Workflows: GPU infrastructure, Linux servers, Docker, AI inference, ComfyUI, Whisper, FFmpeg, Blender rendering, and remote render farm workflows. Automation: Power Automate, Power BI, workflow optimization, scripting, and media transcoding pipelines. Content & Media: Video editing, audio editing/mixing, subtitles, dubbing, voice-over, transcription, localization, and motion graphics. IT & Cloud: Windows, macOS, Microsoft 365, Google Workspace, Exchange, DNS, networking, WordPress, virtual machines, RDP, and cloud applications. I focus on building reliable, scalable solutions that combine IT, automation, AI, and media production to streamline workflows and deliver high-quality results.

@nandu879

Hello, I’m interested in assisting with your AI/GPU infrastructure project. I have a strong understanding of AI compute infrastructure, GPU server architecture, high-performance computing (HPC), and liquid cooling technologies used for modern AI workloads. I can help evaluate GPU server configurations, analyze thermal performance, review cooling architectures (including direct-to-chip liquid cooling and immersion cooling), and provide guidance on scalable AI infrastructure deployment. I’m also familiar with NVIDIA GPU platforms, AI clusters, data center best practices, and the hardware requirements needed for reliable, high-performance AI environments. I focus on delivering practical, technically sound recommendations that improve performance, efficiency, and long-term scalability. Whether you need infrastructure evaluation, architecture review, or technical consultation, I’m confident I can add value to your project. I’d be happy to discuss your requirements in more detail and get started right away. Thank you, and I look forward to hearing from you.

@priyanshuk879

Hi, I can help with AI/GPU infrastructure evaluation and provide practical guidance for building reliable high-performance compute environments. I have experience working with GPU-based systems, server architecture, AI workloads, and infrastructure planning. I can help review GPU server configurations, cooling requirements, thermal performance, and scalability considerations for your AI environment. I understand the challenges around NVIDIA GPU platforms, liquid cooling options like direct-to-chip and immersion cooling, and deploying systems for demanding ML workloads. I can provide clear technical recommendations and help you choose the right architecture based on performance, cost, and future growth. Are you available for a quick chat?

@eternitech

Hi, New on Freelancer — 20 years of development experience behind us. We're taking our first few projects here at a fraction of our normal rate purely to build our review history. You get senior agency work at junior pricing; we get a review. Straight trade. For a high-performance AI/GPU setup, ensuring optimal thermal management is crucial. I'd start by evaluating the current liquid cooling efficiency and the airflow dynamics around your GPUs. This often uncovers hidden bottlenecks affecting system performance. Could you share access details or any specific cooling challenges you've encountered so far?

@MthokoD

Hey there, I noticed your emphasis on liquid cooling solutions for GPU systems, which is a critical yet often overlooked aspect in AI infrastructure. It’s worth flagging that the right thermal management can significantly enhance performance and longevity. The core challenge here is ensuring that your GPU architecture not only meets performance benchmarks but also maintains optimal thermal conditions under heavy loads. This nuanced understanding is essential for achieving reliable AI workloads. I can deliver a robust AI infrastructure that maximizes efficiency while minimizing downtime. My approach emphasizes thorough evaluation and tailored configurations, ensuring you get the most out of your GPU clusters. I see you require expertise in direct-to-chip liquid cooling and immersive solutions. My hands-on experience with NVIDIA GPU technologies and HPC systems positions me to address these needs effectively. A common pitfall in projects like yours is underestimating the complexity of scalable deployments, which can lead to costly setbacks when hiring less experienced freelancers. The next step to scope this project would be a free consultation where I can provide actionable insights tailored to your specific requirements. This will allow you to gauge my approach and expertise without any commitment. Thank you for your time Warm Regards Mthoko

@bhargav922002

Hello, I'm bharghav, with a decade of experience in Electrical Engineering, Machine Learning, and Artificial Intelligence, specifically matching job skills. My background aligns well with the intricacies of high-performance computing systems. I understand your need for an AI/GPU Infrastructure Specialist. My expertise in GPU architecture, liquid cooling solutions, and AI server configurations, especially with NVIDIA GPU technologies and HPC systems, will be instrumental. I can provide precise technical evaluation and guidance for your liquid-cooled GPU systems and scalable AI compute environments. Let's connect in chat to discuss this further.

@markf133

I manage 1,000+ live GPU nodes daily at Cirrascale Cloud Services — NVIDIA H100 SXM5, RTX 4090, and AMD MI300X — with liquid-cooled HGX-class systems as my standard operating environment. Not theory; production infrastructure at scale. I've resolved failures directly relevant to your scope: H100 thermal cascades where rear GPUs ran 15–20°C hotter than front GPUs due to preheated HGX baseboard airflow; a PSU safety reboot triggered when combined Weka daemon and GPU burn draw exceeded 9,057W on an 8,800W system; MI300X RCCL collective failures from NUMA asymmetry; and an HGX B300 GPU tray absent simultaneously at OS, PCIe, BMC, firmware, and thermal sensor levels. My triage library covers Supermicro, ASUS, KAYTUS, Cisco UCS, Dell XE9680, and Lenovo ThinkSystem — across both NVIDIA and AMD stacks. I also build the tooling: internal firmware/driver lookup systems, shift handoff automation, NOC documentation suites, and RMA guides — all used across a live fleet of 1,000+ nodes. This is the depth of documentation and operational rigour I'd bring to your technical evaluation. 18 years enterprise Linux. Certifications: Red Hat, DCAA, CompTIA Linux+, Google Cloud Professional, Security+, Cisco, AWS. Cape Town (UTC+2) — strong daily overlap with AEST business hours. Which GPU platform and cooling architecture are you evaluating? I can go deep on the specifics immediately. — Mark Lloyd Fester | Senior NOC/GPU Infrastructure Engineer, Cirrascale Cloud Services | $25/hr

@prathamd58

Hi — this maps well onto work I've already done. I designed and deployed a CUDA-based GPU Monte Carlo pricing engine (European/Asian/barrier/American options, Longstaff-Schwartz) achieving ~50–100x GPU speedup over CPU baselines with ~80–90% kernel occupancy — which required tuning warp divergence, memory access patterns, and thermal/power headroom to sustain that occupancy under continuous load, the same class of problem as keeping GPU clusters stable under sustained AI training/inference. More directly relevant: I've deployed and optimized GPU infrastructure for a live HFT system trading on the NSE — this involved balancing raw GPU compute throughput against latency-sensitive, always-on workloads, plus the Linux-level hardware tuning (NUMA-aware placement, IRQ/CPU isolation, hugepages) that liquid-cooled AI clusters also depend on for consistent thermal and I/O performance under load. What I'd bring here: technical evaluation of GPU server configs and direct-to-chip vs. immersion cooling tradeoffs against your workload profile, thermal/power headroom analysis so cooling capacity isn't over- or under-provisioned, and infrastructure recommendations (Docker/Kubernetes-based orchestration) that keep the cluster scalable as workloads grow — informed by hands-on production deployment experience, not just spec-sheet comparisons. Happy to start with a quick scoping call to understand your target GPU platform and workload mix.

@moosamemonn

This reads like a hardware and thermal engineering role focused on liquid-cooled GPU clusters, so I'd rather be upfront than bid blindly. My background is in AI/ML software, building GPU-backed training and inference systems, including concurrent multi-agent workflows and RAG pipelines. I understand compute and memory requirements from the workload side, what drives GPU utilization, how different model sizes affect throughput, and where inference bottlenecks typically appear. I don't have hands-on experience designing liquid cooling, immersion systems, or data center thermal infrastructure. If your goal is translating AI workload requirements into practical infrastructure specifications that a hardware specialist implements, I can genuinely help. I can recommend GPU configurations based on workload characteristics, identify likely performance bottlenecks, and align infrastructure with your AI use case. As a final-year AI student, I also stay current with modern models, deployment patterns, and GPU computing. That combination of practical AI development and up-to-date theoretical knowledge lets me contribute meaningfully to infrastructure planning, even if I'm not the person designing the cooling system itself. If the role is primarily thermal engineering, you're likely better served by a data center hardware specialist. If it's centered on AI workload planning and infrastructure decisions, I'd be happy to discuss how I can help.

@ashiqiitkgp

Hi there, As an AI Systems Architect and Infrastructure Specialist with deep experience in GPU co-design, high-performance computing (HPC), and thermal management, I am well-equipped to provide technical evaluation and guidance for your liquid-cooled GPU compute platform. How I Can Support Your Technical Evaluation: Cooling Architecture & Thermal Performance: I can evaluate Direct-to-Chip (DTC) cold-plate vs. Single/Two-Phase Immersion Cooling setups, factoring in coolant flow rates, CDU (Cooling Distribution Unit) integration, thermal design power (TDP) thresholds for high-density NVIDIA HGX/H100/B200 platforms, and heat-rejection infrastructure. Server & Cluster Infrastructure Sizing: I will analyze host-to-GPU interconnect topologies (NVLink/NVSwitch, PCIe Gen 5) and high-speed networking requirements (InfiniBand/RoCE v2) to ensure your thermal solution doesn't create data-throughput bottlenecks. Scalable AI Deployment Strategy: I will provide clear technical guidance on power density (kW per rack), PUE optimization, hardware fail-safes, and containerized workload scheduling (Kubernetes/Docker) tailored for high-density AI clusters. Let's connect to discuss your specific server configurations and target rack power density requirements. Best regards,