L3 Technical SME (AI Compute) / L3 GPU (AI Infrastructure & GPU Acceleration) | AMK Groups | Remote / Indonesia

AMK Groups; Indonesia; Remote; IDR 2,999,129,000 - 5,998,258,000; Full time

Job summary

AMK Groups seeks an L3 Technical SME (AI Compute) / L3 GPU for a contract role with full remote work flexibility. Responsibility includes owning AI compute architectures, GPU hardware diagnostics, and high-speed fabric interconnects, deploying large-scale GPU clusters (NVIDIA H100/A100).

You will tune AI training performance, collaborate with researchers and data-center teams, and communicate with recruiters and candidates. This is a contract engagement offering international project exposure.

Qualifications

• Bachelor’s degree in CS/CE/EE/AI or related field.
• 6–8 years in HPC, AI infrastructure, or GPU systems engineering.
• Experience deploying enterprise NVIDIA GPU clusters, InfiniBand fabrics, and AI compute nodes.
• Proficient in Linux systems administration and kernel tuning.
• Hands-on with distributed training frameworks and containerized GPU execution (NVIDIA Container Toolkit).
• Strong debugging, problem solving, and stakeholder communication.
• Legal work authorization for remote work.

Responsibilities

• Provide expert-level third-line support for enterprise AI compute clusters and GPU infrastructure.
• Architect, deploy, configure, and optimize high-performance GPU clusters (NVIDIA H100/A100).
• Design and troubleshoot ultra-low latency fabric interconnects using InfiniBand and RoCE.
• Administer CUDA drivers, NCCL, PyTorch/TensorFlow environments, and containerized runtimes.
• Diagnose and resolve complex GPU hardware faults and fabric bottlenecks.
• Collaborate with AI researchers, MLOps, and data center teams to maximize efficiency.
• Establish benchmarking, stress testing, and profiling for large-scale training workloads.
• Maintain technical documentation, architecture blueprints, runbooks, and guides.

Skills

HPC experience

AI infrastructure

GPU systems

Linux admin

NVIDIA GPUs

NCCL optimization

Container runtimes

Distributed training

Networking InfiniBand

RoCE RDMA

Slurm

Kubernetes

Terraform

Ansible

Education

Bachelor's degree in CS/CE/EE/AI

Tools

NVIDIA Container Toolkit

Docker

Singularity

DCGM

Prometheus

Grafana

Slurm

Kubernetes

Terraform

Ansible

Job description

Position Summary

Driving advanced artificial intelligence compute architecture, high-performance GPU cluster engineering, and distributed machine learning infrastructure globally, AMK Groups is actively seeking an accomplished L3 Technical SME (AI Compute) / L3 GPU for a premier contract professional engagement featuring flexible remote work options. In this vital expert technical role, you will take full operational, tactical, and technical ownership of enterprise GPU accelerator integration, high-performance computing (HPC) fabric orchestration, CUDA/ROCm software stacks, and AI cluster performance tuning. Bringing direct data center and AI infrastructure experience, you will empower an elite technology enterprise to achieve uncompromised compute throughput, ultra-low latency cluster interconnects, and superior AI model training velocity. This prestigious career opportunity offers competitive remuneration, international project exposure, and professional growth within a leading global data center and AI infrastructure enterprise.

Detailed Job Description

As an L3 Technical SME (AI Compute) / L3 GPU supporting AMK Groups on a contract basis (with full remote work flexibility available), you will take full operational, tactical, and technical ownership of complex AI compute architectures, GPU hardware diagnostics, high-speed InfiniBand/RoCE networking, and cluster troubleshooting. Your day-to-day responsibilities include architecting, deploying, and optimizing large-scale GPU compute clusters (NVIDIA H100/A100/B200 platforms), configuring distributed training frameworks and deep learning libraries, troubleshooting low-level hardware faults, driver/firmware mismatches, and fabric bottlenecks, collaborating closely with AI researchers, systems architects, and data center engineering teams, and communicating directly with technical recruitment leads like Santhosh. Furthermore, you will manage application requirements by submitting your updated CV via direct message or email to Santhosh at [e-mail] or contacting via phone at [phone].

Key Responsibilities

• Provide expert-level technical leadership and third-line support for enterprise artificial intelligence compute clusters and GPU infrastructure.
• Architect, deploy, configure, and optimize high-performance GPU accelerator hardware (NVIDIA H100, A100, Tensor Core architectures).
• Design and troubleshoot ultra-low latency fabric interconnects utilizing InfiniBand (HDR/NDR) and RoCE (RDMA over Converged Ethernet).
• Administer CUDA drivers, NCCL communication libraries, PyTorch/TensorFlow execution environments, and containerized AI runtimes (Docker/Singularity).
• Diagnose and resolve complex GPU hardware faults, PCIe bus errors, thermal throttling, memory ECC errors, and fabric bottlenecks.
• Collaborate proactively with AI research scientists, MLOps engineers, and data center infrastructure teams to maximize cluster compute efficiency.
• Establish rigorous benchmarking, stress testing, and profiling suites for large-scale distributed model training workloads.
• Maintain meticulous technical documentation, AI cluster architecture blueprints, troubleshooting runbooks, and performance optimization guides.

Required Qualifications & Skills

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, or related technical discipline.
• Minimum of 6 to 8 years of progressive professional hands-on experience in high-performance computing (HPC), AI infrastructure, or GPU systems engineering.
• Direct, demonstrable operational expertise in deploying and managing enterprise NVIDIA GPU clusters, InfiniBand fabrics, and AI compute nodes.
• Comprehensive working knowledge and practical proficiency in Linux systems administration, kernel tuning, and low-level hardware diagnostics.
• Deep practical experience with distributed training frameworks, NCCL optimization, and containerized GPU execution (NVIDIA Container Toolkit).
• Solid practical grasp of network fabrics, BGP/RoCE routing, and high-throughput storage architectures (GPUDirect).
• Exceptional analytical problem-solving aptitude, root-cause debugging capabilities, and professional stakeholder communication skills.
• Mandatory legal work authorization with flexible remote work eligibility (open to any candidates for remote work).

Nice-to-Have Skills

• Professional certifications such as NVIDIA Certified Deep Learning Associate or Linux Foundation Certified Systems Administrator (LFCS).
• Prior professional working experience supporting hyperscale AI cloud providers, supercomputing centers, or enterprise LLM training facilities.
• Hands-on familiarity with Kubernetes GPU operator management, Slurm workload manager, and cloud orchestration tools (Terraform, Ansible).
• Experience utilizing AI cluster monitoring and observability suites (DCGM, Prometheus, Grafana).
• Active participation in AI infrastructure open-source projects, PyTorch developer communities, or HPC standards committees.

Recruiter: AMK Groups Recruitment Division

Contact Name: Santhosh (Technical Recruitment Lead)

Email: [e-mail]

Phone: [phone]

Company Website: https://www.amktechnology.com

Salary/Rate: Market Competitive / Enterprise AI Compute SME Contract Package

Work Schedule: Contract Engagement / Remote Work Options Available

Deadline: Open until filled (Urgent L3 AI Compute / GPU SME Opening)

Notice Period: Immediate to 15 Days Preferred

Contract Duration: Contract Role (Remote / Indonesia)

Recruitment Pro Tip

When applying for this L3 Technical SME (AI Compute) position through AMK Groups, ensure your resume explicitly highlights your NVIDIA GPU cluster tenure, InfiniBand/RoCE fabric expertise, and distributed AI training optimization background.