Join VultrThe GPU-focused Technical Account Manager (TAM) leads the post-sales technical success of customers deploying large-scale AI, training, inference, and high-performance GPU workloads on the company's platform. This includes customers using NVIDIA GPU clusters, AMD GPU clusters, GPU VMs, and rack-scale bare-metal environments.
You will act as a trusted advisor across LLM training, fine-tuning, RAG workloads, distributed training frameworks, storage throughput requirements, multi-GPU scaling, and performance tuning. This role requires deep technical fluency and exceptional customer management skills to help AI/ML teams achieve predictable, cost-efficient, high-performance outcomes.
Key ResponsibilitiesAI/GPU Onboarding & Workload Architecture- Lead onboarding for customers deploying GPU clusters (bare metal, VMs, or hybrid).
- Advise on cluster design: multi-GPU topology, NVLink/NVSwitch considerations, RDMA, Infiniband and RoCE Ethernet, networking throughput, and storage IOPS requirements.
- Guide customers in selecting GPU types and configurations based on workload (training, fine-tuning, inference, embeddings, RAG pipelines).
- Support distributed frameworks: PyTorch, TensorFlow, DeepSpeed, Megatron, JAX, Ray, Mosaic, HuggingFace, etc.
- Advanced hands on Kubernetes skills
- Advanced hands on SLURM skills
Performance Optimization & Scaling- Identify bottlenecks (network, storage, memory bandwidth).
- Provide tuning recommendations for batch size, mixed precision, parallelization strategies, and checkpointing.
- Help customers evaluate cost vs. performance tradeoffs (GPU mix, CPU pairing, instance types, cluster sizing).
Technical Relationship Ownership- Own the long-term technical strategy across assigned GPU/AI accounts, including hyperscalers, labs, and high-growth AI startups.
- Host recurring technical review meetings, roadmap reviews, and optimization sessions.
- Define scaling plans, future GPU reservation needs, and capacity forecasting.
- Incident & Escalation Management
- Partner with Support, SRE, Networking, NOC, and Product Management & Engineering to resolve high-urgency incidents.
- Manage outage communications, corrective action plans, and postmortem reviews with customers.
- Advocate for GPU reliability improvements and influence roadmap priorities.
Account Growth & Expansion- Identify opportunities for expanded clusters, high speed storage, or networking upgrades.
- Support Sales with technical validation and architecture diagrams needed for expansion.
Customer Advocacy & Product Feedback- Provide structured feedback on existing and future GPU offerings, networking fabrics, storage platforms, and upcoming AI/ML platform features.
- Partner with Product on early access programs (new GPUs, pipelines, orchestration, etc.).
Qualifications- 2-5+ years as an AI/ML Engineer, AI/ML Ops, Technical Account Manager, HPC Engineer, Sales/Solutions Engineer or relevant technical role.
- Strong knowledge of GPU hardware architectures (NVIDIA/AMD), CUDA/ROCm, distributed training, and ML frameworks.
- Experience with Linux tuning, networking (Infiniband, RoCE fabrics).
- Experience with high-performance storage systems (DDN, NetApp, Vast, Weka, etc.).
- Ability to communicate complex concepts clearly to both executives and engineering teams.
- Prior experience supporting hyperscale, AI labs, or large cluster deployments is a plus.
- Cloud Native Computing Foundation Certified Kubernetes Administrator (CKA) certification is a plus.
Compensation$115,000 - $140,000
This salary can vary based on location, years of experience, background and skill set.
