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AI Architect

Vaga não está no LinkedIn

🕒 Outubro 21

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🔴 Especialista

🤖 Engenheiro de IA

🗣️🇺🇸🇬🇧 Inglês obrigatório

De onde vem esta vaga

Publicada na página de carreiras da Insight Softmax Consulting, não em um site de vagas

Vista pela primeira vez pelo Remote Rocketship Outubro 21

Ainda aberta no site da Insight Softmax Consulting. Verificada 4 horas atrás.

Logo of Insight Softmax Consulting

Insight Softmax Consulting

11 - 50 funcionários

Fundada em 2016

💼 Consultoria

🤖 Inteligência Artificial

🤝 B2B

Consulting • Artificial Intelligence • B2B

A Insight Softmax Consulting é uma empresa de consultoria focada em dados que combina data science, software engineering e high-performance computing para resolver problemas de negócios e pesquisa de ponta a ponta. A empresa prioriza a definição dos problemas de negócio e, a partir disso, desenvolve soluções em data analytics, AI/ML (incluindo generative AI e treinamento de LLMs) e infraestrutura HPC para a etapa final, como cloud-native HPC e accelerated computing para CFD e workloads científicos avançados. Também oferece expertise e serviços em open source para tornar recursos avançados de computação e AI acessíveis a empresas e organizações de pesquisa. A empresa possui escritórios em São Francisco, nos Estados Unidos, e em Zurique, na Suíça.

Descrição

• Lead technical discovery with customers and translate business goals into AI platform architectures, phased roadmaps and effort estimates • Design inference serving platforms on Kubernetes and bare metal, including model serving, GPU scheduling and partitioning, autoscaling, multi-tenancy and capacity planning • Design AI gateway and routing layers with tenant-aware routing, model pools, budgets and quotas, rate limiting, observability and multi-site failover • Define reference architectures for multi-tenant GPU clouds, sovereign and air-gapped deployments, and hybrid cloud and on-premises estates • Advise on AI usage governance, including cost visibility, token accounting, audit, data handling and security posture for LLM services • Evaluate and recommend build, buy or compose decisions across open-source and commercial AI infrastructure components • Prototype, validate assumptions in a lab and review implementations delivered by AI and platform engineers • Own the technical quality of project outcomes • Represent Insight Softmax in customer architecture reviews, partner enablement sessions and executive readouts • Support pre-sales scoping and estimates • Reserve time each week for pre-sales support, internal platform work and mentoring

🎯 Requisitos

• At least 8 years in infrastructure, platform or ML engineering • At least 3 years designing and operating production AI or ML platforms at scale • Hands-on experience deploying LLM inference in production, including tensor and pipeline parallelism, batching, caching and performance tuning • Deep understanding of NVIDIA and AMD accelerators, drivers and runtimes, GPU scheduling on Kubernetes, high-speed interconnects and storage for AI workloads • Experience designing AI gateway or API management layers • Strong Kubernetes and Linux skills; able to read and debug the stack from the scheduler down to the node • Deep knowledge of at least one of AWS, GCP, or Azure; preferably AWS • Track record of leading architecture engagements with enterprise customers, including writing proposals, estimates and architecture documents that engineers can execute against • Clear written and spoken communication with both engineers and executives • 3 references will be required • Optional: Experience at an AI lab, AI-native company, neocloud, or building platform products for them • Optional: Multi-tenant GPU cloud design, Slurm or other batch schedulers, RAG, agentic systems, model evaluation, fine-tuning pipelines, air-gapped or FIPS deployments, Spectro Cloud Palette and PaletteAI, Run:ai, observability for AI services • Bonus: Python, Go or Rust; software engineering background; published talks, blog posts or open source contributions in AI infrastructure; using Linux as a primary desktop workstation environment

🏖️ Benefícios

• Remote work environment • Occasional travel to customer sites in the US for architecture workshops, load tests and go-live reviews

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