Strategic Technical Account Manager GPU at Jobgether – United States

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Strategic Technical Account Manager GPU in United States.

This role sits at the intersection of advanced GPU infrastructure, AI/ML workloads, and strategic customer success, supporting organizations building large-scale AI systems. You will act as a trusted technical advisor for customers deploying GPU-intensive workloads such as LLM training, fine-tuning, inference, and distributed AI pipelines. The position blends deep technical expertise with customer-facing leadership, ensuring that high-performance computing environments are optimized for scalability, cost efficiency, and reliability. You will work closely with AI labs, startups, and enterprise teams to design architectures, resolve performance challenges, and guide long-term infrastructure strategy. The environment is highly technical and fast-paced, requiring strong fluency in GPU systems, cloud infrastructure, and AI frameworks. This is a high-impact role where your guidance directly influences how customers build and scale modern AI systems.

You will serve as the primary technical partner for GPU-focused customers, guiding them through architecture design, onboarding, optimization, and long-term scaling of complex AI workloads.

• Lead onboarding and deployment of GPU clusters across bare metal, virtualized, and hybrid environments
• Design and advise on GPU architecture, including multi-GPU topology, networking (RDMA, Infiniband, RoCE), and storage requirements
• Support customers using distributed AI frameworks such as PyTorch, TensorFlow, DeepSpeed, JAX, Ray, and HuggingFace
• Optimize performance across training and inference workloads, identifying bottlenecks and improving efficiency and cost structure
• Act as the long-term technical owner for key accounts, leading roadmap discussions, capacity planning, and scaling strategy
• Manage technical escalations and coordinate with internal engineering, support, and infrastructure teams to resolve critical incidents
• Provide architecture guidance and support sales teams with technical validation for expansions and upgrades
• Gather and relay structured customer feedback to influence product development and future GPU platform improvements

You bring strong hands-on experience in AI/ML infrastructure, GPU systems, and customer-facing technical roles, with the ability to bridge deep engineering and strategic advisory work.

• 2–5+ years of experience in AI/ML engineering, MLOps, solutions engineering, HPC, or technical account management roles
• Strong understanding of GPU architectures (NVIDIA/AMD), CUDA/ROCm, and distributed training systems
• Experience with AI/ML frameworks such as PyTorch, TensorFlow, or similar distributed compute tools
• Knowledge of Linux systems, networking technologies (Infiniband, RoCE), and performance tuning
• Experience with high-performance storage systems and data-intensive AI workloads
• Ability to design scalable infrastructure for training, inference, and large-scale AI pipelines
• Strong communication skills, able to translate complex technical topics for both engineers and executive stakeholders
• Experience working with hyperscalers, AI labs, or large-scale compute environments is a strong plus
• Kubernetes certification (CKA) or similar cloud-native expertise is a plus

• Competitive salary range: $115,000 – $140,000 (based on experience and location)
• Comprehensive health coverage with medical, dental, and vision plans
• 401(k) plan with employer matching and immediate vesting
• Paid time off, holidays, and structured PTO growth with tenure
• Sabbatical program and additional anniversary-based rewards
• Remote work support including home office stipend and internet reimbursement
• Wellness benefits including gym reimbursement and wellness platform access
• Professional development budget for learning and certifications
• Inclusive, global work environment focused on innovation in AI infrastructure