Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Выше рынка
$250к-320к/год
$200к$230кмедиана$270к
По похожим ролям (49) ~ $230к/год
На СНГ рынке: $5.4к/мес ($3.5к - $5.9к)
91
Крутая вакансия
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Высокая зарплата, чёткая задача для первой роли такого типа и работа с передовой AI-инфраструктурой делают вакансию привлекательной, хотя у стартапа больше неопределённости, чем у зрелой компании.
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Риски стартапаШирокая самостоятельностьЗарплата выше рынкаПередовой AIПоездки к клиентам
Оценка от Hirify AI
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Founding Solutions Architect (AI): Designing and validating production architectures for customer training, post-training, and inference workloads on Prime Intellect infrastructure with an accent on GPU compute, distributed systems, benchmarking, and technical discovery. Focus on building reproducible POC frameworks, comparing latency, throughput, utilization, and cost against customer baselines, and creating scalable solutions-architecture playbooks.
Location: United States; remote or San Francisco, with travel to customer sites as needed
Salary: $250,000–$320,000 plus meaningful equity
Company
hirify.global is building an open superintelligence stack that combines compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for frontier AI teams.
What you will do
Lead technical discovery across training, post-training, and inference workloads.
Design production-ready customer architectures on hirify.global infrastructure and partner with engineering on migration and deployment.
Own workload benchmarks and proofs of concept against customer baselines and competitive alternatives.
Translate latency, throughput, utilization, and cost results into technical business cases for ML engineers and executive buyers.
Build benchmark methodologies, reference architectures, POC frameworks, and adoption playbooks for Model Factory.
Requirements
Strong background in ML infrastructure, distributed systems, cloud, or GPU computing.
Working knowledge of modern training and inference stacks, CUDA/GPU environments, and model-serving patterns.
Customer-facing experience in solutions architecture, sales engineering, forward-deployed engineering, or a similar role.
Ability to communicate fluently with ML engineers and executive stakeholders.
Strong ownership and a preference for validating claims with real customer workloads and benchmarks.
Experience using LLMs, automation, and programmatic tools to work efficiently.
Nice to have
Experience with distributed training technologies such as FSDP, Megatron, or DeepSpeed, or high-throughput inference with vLLM, SGLang, or TensorRT-LLM.
Experience benchmarking H100, H200, or GB200 hardware and InfiniBand or RoCE interconnects.
Background at a GPU cloud, neocloud, hyperscaler AI team, or frontier lab infrastructure team.
Experience building a solutions or forward-deployed function from scratch.
Culture & Benefits
Visa sponsorship and relocation support.
Flexible remote work or work from San Francisco.
Travel to customer sites as needed.
Professional development budget.
Team off-sites and conferences.
Meaningful equity and the opportunity to build infrastructure for open AI.
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