Hire the Best Cluster Computing Developers
in Pakistan

I build cloud-native data platforms at scale. Lakehouses, streaming systems, AI infrastructure. My clients are companies where bad data or downtime isn't an option. I have 6 years of experience designing and delivering greenfield data architectures for Fortune 100 enterprises across fintech, healthcare, and identity management. Most recently, I migrated a fintech platform off a single monolithic server onto a distributed lakehouse on AWS with Spark, Airflow, and Apache Iceberg. That cut pipeline runtimes by 50% and infrastructure costs by 40%. Here's what I work with: Lakehouse & batch: Spark, PySpark, Databricks, Iceberg, Hudi, Trino, Airflow Streaming & CDC: Kafka, Debezium, ksqlDB, Spark Structured Streaming, ClickHouse Cloud: AWS (EKS, EMR, Glue, Lambda, SageMaker), Azure (AKS, Databricks, AI Foundry) Infrastructure: Kubernetes, Terraform, Helm, Docker, GitHub Actions CI/CD Governance: Apache Ranger, RBAC, row-level security, HIPAA/GDPR/SOC 2 AI/ML infra: RAG pipelines, vector databases (Pinecone), LLM-backed applications I've contributed to open-source projects like Debezium (Red Hat's CDC platform) and Mage.ai. I work independently, communicate proactively, and I'm used to collaborating remotely across US, EU, and Middle East time zones. If you need someone who can own the architecture end to end, not just write pipelines, let's talk.

I build the infrastructure that makes AI actually work in production. I work across the whole stack, from bare metal GPUs and Kubernetes to LLM serving, inference optimization, AI agents and the applications running on top of them. 🔹100% Job Success | Top Rated 🔹60+ LLM deployments 🔹30+ GPU Kubernetes clusters 🔹30+ AI servers designed and deployed 🔹20+ NVIDIA GPUs deployed in a single cluster. I wrote the IaC for GPU cluster orchestration on KAUST Shaheen III, one of the world's leading supercomputers. That is the level of infrastructure I work with, both on prem and in the cloud. Most of my work is around self hosted and private AI, GPU infrastructure, LLM deployment and making AI systems reliable enough for real production use. 🔹I work hands on with: 🔹Self hosted LLMs and model serving: vLLM, NVIDIA Triton, TensorRT, SGLang, Ollama, Qwen, Llama, DeepSeek and other open source models 🔹GPU inference optimization: FP8, INT8, FlashAttention, tensor parallelism, batching, quantization and GPU performance tuning 🔹GPU Kubernetes: NVIDIA GPU Operator, Proxmox, Rancher, K3s, OpenShift, Calico, MetalLB, HAProxy and multi GPU scheduling 🔹Cloud AI infrastructure: AWS, GCP, Azure, GKE, EKS, AKS, Vertex AI, SageMaker and GPU compute 🔹AI agents and applications: LangGraph, LangChain, CrewAI, Claude Agent SDK, MCP, RAG, document intelligence and voice agents 🔹MLOps and platform engineering: Terraform, Ansible, Pulumi, Helm, Kubeflow, Ray, GitHub Actions, GitLab CI, ArgoCD, Flux, Prometheus, Grafana and OpenTelemetry 🔹A few results from projects I've worked on: Reduced LLM inference latency from 3.2 seconds to 800ms through vLLM and serving optimization Reduced a client's monthly cloud bill from $10K to $4K Served LLM workloads for 1,000+ concurrent users on bare metal Kubernetes with zero unplanned downtime for 12 months Built and deployed a Docling + GraphRAG pipeline on GCP for commercial real estate lease analysis 🔹Clients have described my work as: "single handedly built our Kubernetes infrastructure for our GPU setup" "a full stack AI guy" "gets concepts quickly and is an incredibly hard worker" "when he says he'll do it by a deadline, he does" "approaches the project as if it were his own" "incredibly efficient" I'm currently CTO / AI Infrastructure Lead at Peregrine Ventures AI, where I work hands on with production AI systems. I also run my own dual RTX Pro 6000 Blackwell server with EPYC, Proxmox and GPU passthrough, so on prem GPU infrastructure isn't something I just know from the cloud. It's something I work with every day. If you're building, deploying, self hosting, scaling or optimizing an AI or LLM system, feel free to reach out. I'm happy to look at the architecture, figure out what is actually needed and help get it into production.

🧠 PHD ACADEMIC EDITOR & RESEARCH SPECIALIST Need expert assistance with a research paper, thesis, systematic review, journal revision, or academic formatting? I am a PhD-qualified Computer Science researcher, university faculty member, and Top Rated Plus freelancer with 15+ years of academic and research experience. I help researchers, doctoral scholars, universities, and professionals strengthen manuscripts for Scopus, Web of Science, IEEE, Springer Nature, Elsevier, Taylor & Francis, Wiley, MDPI, and other peer-reviewed journals. ✔ Top Rated Plus Freelancer ✔ 100% Job Success Score ✔ $20K+ earned on Upwork ✔ 1,500+ completed Upwork hours ✔ Experience supporting peer-reviewed publications 📄 RESEARCH PAPERS & JOURNAL PUBLICATION • Research-paper editing and technical improvement • Q1, Scopus, Web of Science, SCI, ESCI, and IEEE manuscripts • Journal selection and author-guideline compliance • Major and minor manuscript revisions • Reviewer-comment analysis and rebuttal letters • Cover letters, highlights, and declarations • Submission, resubmission, and production-stage support 🎓 THESIS & DISSERTATION SUPPORT • PhD and master’s thesis/dissertation editing • Literature-review development and improvement • Research gaps, objectives, questions, and hypotheses • Qualitative, quantitative, and mixed-methods research • Methodology development and evaluation • Results interpretation and discussion improvement • University-template compliance 📚 SYSTEMATIC REVIEWS • Systematic literature reviews and PRISMA 2020 • Search strategies and eligibility criteria • Study screening and data extraction • Quality assessment and evidence tables • Thematic synthesis and research-gap identification • Bibliometric analysis and meta-analysis support 📝 ACADEMIC EDITING & FORMATTING • Proofreading, language editing, and rewriting • APA 7, IEEE, Harvard, Chicago, and MLA • Citation and reference-list verification • DOI and bibliographic-detail checking • Microsoft Word thesis and manuscript formatting • Automatic TOC, heading numbering, captions, and cross-references • EndNote, Mendeley, Zotero, and LaTeX support 🔬 RESEARCH AREAS Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, LLMs, Cybersecurity, IoT, Blockchain, FinTech, Cloud and Edge Computing, Data Science, Smart Cities, Intelligent Transportation, Industry 4.0, and Software Engineering. 💡 MY APPROACH I provide ethical, rigorous editing, research guidance, formatting, and publication support based on the authors’ legitimate research, data, findings, and intellectual contributions. 📩 LET’S WORK TOGETHER Send me your manuscript, thesis, reviewer comments, or formatting requirements to discuss the best approach for your project.

Tired of fragile infrastructure, unpredictable deployments, and cloud bills that keep climbing? I turn chaotic, manual environments into disciplined, automated, and security-hardened platforms that scale calmly under real pressure. I work at the intersection of Architecture, Execution, and Security. With over six plus years of experience, I don’t just build pipelines; I design systems around business constraints, traffic patterns, and strict compliance needs like FedRAMP and PCI DSS. From stabilizing AWS environments for enterprise stakeholders like Apple & eBay to scaling government platforms for 50k concurrent users, I ensure your infrastructure is a business asset, not a bottleneck. 𝐓𝐡𝐞 𝐕𝐚𝐥𝐮𝐞 𝐈 𝐁𝐫𝐢𝐧𝐠 𝐭𝐨 𝐘𝐨𝐮𝐫 𝐓𝐞𝐚𝐦: • Rapid Environment Provisioning: Reduced spin-up times by ~80% using Terraform and automated multi-account baselines. • Operational Resilience: Reduced stability incidents from weekly to near-zero through custom Kubernetes remediation playbooks. • Cost & Compliance: Optimized cloud spend (e.g., AWS Macie) while driving remediation for vulnerabilities across IAM, networking, and clusters. • Faster, Safer Delivery: Integrated security checks (Trivy, SonarQube) into CI/CD pipelines to move from reactive firefighting to predictable, secure operations. 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞: I specialize in building production-ready platforms using a modern, secure-by-default stack: Cloud Platforms: AWS (EKS, ECS, IAM, VPC), Oracle Cloud (OCI/OKE), and Azure (AKS). Orchestration & GitOps: Kubernetes, Helm, Argo CD, and Istio. Infrastructure as Code: Advanced Terraform, Terragrunt, CloudFormation, and Ansible. CI/CD & Automation: GitHub Actions, Jenkins, GitLab CI, and Bitbucket Pipelines. Observability & Security: Prometheus, Grafana, ELK, Orca Security, Kyverno, and OCI Cloud Guard. 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐞𝐝 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞: ✓ Certified Kubernetes Application Developer (CKAD) ✓ AWS Certified Solutions Architect – Associate ✓ AWS Certified Developer – Associate ✓ HashiCorp Certified: Terraform Associate 𝐖𝐡𝐚𝐭 𝐈 𝐃𝐞𝐥𝐢𝐯𝐞𝐫: I don’t just configure tools; I build structured DevSecOps systems. Whether you need an AWS multi-account landing zone, a PCI DSS-aligned migration, or a Kubernetes security overhaul, I provide a clear, structured path forward. If you’re looking for someone who can bring clarity to complexity and help your platform scale without chaos, click Invite or Send a Message. 𝐋𝐞𝐭’𝐬 𝐛𝐮𝐢𝐥𝐝 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐭𝐡𝐚𝐭 𝐡𝐮𝐦𝐬 𝐪𝐮𝐢𝐞𝐭𝐥𝐲 𝐢𝐧𝐬𝐭𝐞𝐚𝐝 𝐨𝐟 𝐬𝐜𝐫𝐞𝐚𝐦𝐢𝐧𝐠 𝐚𝐭 𝟑 𝐀𝐌!

I fix broken servers, harden insecure infrastructure, and deploy production-ready cloud environments on AWS, GCP, and DigitalOcean - typically within 48 hours. Top Rated freelancer. 100% Job Success Score. Clients bring me unmanaged VPS instances, misconfigured Docker containers, and infrastructure failing under load. I hand back hardened, fast, production systems running at 99.9% uptime. 𝐖𝐡𝐚𝐭 𝐈 𝐝𝐞𝐥𝐢𝐯𝐞𝐫: Server Rescue & Troubleshooting e-mergency fixes for crashed servers, disk failures, boot issues, data recovery on Linux (Ubuntu, Debian, CentOS, AlmaLinux) Security Hardening - SSH lockdown, iptables/UFW firewall configuration, SSL/TLS setup, VPN tunnels, system call auditing, and strict access controls Cloud Infrastructure - AWS (EC2, S3, RDS), GCP, and DigitalOcean architecture, migration, and cost optimization. Reduced cloud spend by 35% on past projects through right-sizing and Terraform (IaC) Docker & Kubernetes - container orchestration, Docker Compose stacks, Kubernetes cluster management, and production deployments for MERN, Python, and Java applications CI/CD Pipelines - GitHub Actions, GitLab CI, automated build-test-deploy workflows that cut manual deployment time by 80% Monitoring & Observability - Prometheus, Grafana dashboards, log analysis, and proactive alerting for performance visibility Self-Hosted Open Source - Nextcloud, Supabase, Coolify, and custom self-hosted stacks deployed and maintained on production VPS AI Infrastructure - deployment and configuration of AI tools, LLM pipelines, and GPU-accelerated workloads on cloud servers Recent client results: - Recovered critical data from a failed dedicated server disk (Contabo) under emergency timeline - Deployed and configured Nextcloud AIO with Talk HPB, fixing complex Docker networking and NAT issues - Built a Grafana/Prometheus monitoring stack with five containers and pre-built dashboards - Automated CI/CD pipelines for C++ and game deployment via GitHub Actions and AppVeyor - Set up high-availability PostgreSQL clusters for production environments I communicate clearly, respond within an hour, and document every step so you always know the exact status of your infrastructure. Available for project-based rescues and ongoing retainer engagements. Message me your server or infrastructure challenge; I'll scope a solution within hours.

I help SaaS and AI teams build, migrate and stabilize production Kubernetes on AWS. Platform engineering, EKS, Terraform, CI/CD, cloud migration, cost control, and the GPU and inference infrastructure AI products need. CKA and CKAD, hands-on. Most of my work falls into one of five problems: 1. AI that works on a laptop but not in production. AI agents, LLM and RAG systems that fall over under real traffic. Evals, guardrails, GPU scheduling, inference cost control, CI/CD for models. This is where most AI projects actually die. 2. Kubernetes that keeps breaking. Nodes evicting, deploys that need a human at 2am, no observability. I make clusters boring. 3. Infrastructure you inherited and nobody documented. The original builders are gone, nothing is in code, and you are afraid to touch it. I take it over, map it, get it into Terraform, and hand you back something you can actually change. 4. Cloud bills that grew faster than the product. I cut a Danish SaaS company's spend by 40 percent with Terraform and multi-cloud rightsizing, and held a 99.9 percent SLA through the change. 5. Migration. AWS account to AWS account, on-prem to cloud, cloud to cloud, VM to Kubernetes. Planned, staged, and reversible. Selected work: - Built a multi-tenant Kubernetes platform for a funded UK company: 15+ cloud providers, GPU compute, a 100+ component marketplace. Live in production. - Designed Kubeflow and multi-cloud Kubernetes for a Norwegian ML platform. Still running in production 5+ years later, GDPR compliant. - Ran an on-prem Kubernetes and GPU research cluster for Imperial College London. 100 percent uptime across 2 years, bare metal. - Hardened Kubernetes and IaC for a Saudi fintech under SAMA requirements. - Architected HIPAA-aligned AWS infrastructure for a US healthcare SaaS. Stack: Kubernetes (EKS, AKS, GKE, K3s, RKE2, Rancher), Terraform, ArgoCD, GitOps, GitHub Actions, Helm, Docker, Linux, Istio, Vault, Keycloak, Prometheus, Grafana, Kubeflow, MLflow, PostgreSQL high availability, self-hosted and multi-tenant platforms, n8n, AWS, Azure, GCP, Python, FastAPI. SRE and platform engineering. Compliance: HIPAA, GDPR, SOC 2, SAMA. I work 30+ hours a week with 4 to 6 hours of overlap with US business hours, and I reply within a few hours on weekdays. Two ways to start. A fixed-price Kubernetes and cloud audit: I review your architecture, cost and reliability posture and hand back a prioritized remediation plan you own whether or not we work together. Or embed part-time on an ongoing basis, from 5 to 10 hours a week upward, as your platform engineer. Send me your current architecture or the specific failure you are hitting and I will tell you how I would approach it.