AI Solution Engineer

🕒 Fevereiro 17

🏄 California, New York, +3 estados a mais – Remoto

🏄 California – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🌲 Oregon – Remote 🤠 Texas – Remote

💵 $172.000 - $349.000 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

💻 Engenheiro de Soluções

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

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Hewlett Packard Enterprise

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 2015

🏢 Corporativo

🔧 Hardware

☁️ SaaS

Enterprise • Hardware • SaaS

LinkedIn oficial da Hewlett Packard Enterprise, a empresa global de edge-to-cloud. Compartilhando nossa paixão e propósito por meio da tecnologia e inovação.

Descrição

• Architect, build, and deliver AI solutions in the form of demos and proof-of-concepts for customers during the pre-sales stage. • Lead technical discussions with prospects and partners to propose HPE and partner Integrated solutions that address business challenges and opportunities using AI. • Demo AI solutions to prospects. • Lead Proof-of-Concepts / Proof-of-Value engagements for HPE prospects. • Assist in any product or technical issue towards an initial sale or renewal of a customer. • Help enable prospects, partners, and internal HPE teams on HPE's value in the AI landscape.

🎯 Requisitos

• Bachelor's, Master's or other Advanced degree in Engineering, Computer Science, or similar quantitative focus. • 4 years + experience working with Machine Learning or Deep Learning. • Experience working with Kubernetes. • Competency working with the latest LLM frameworks, both Open Source (e.g. LangChain, LllamaIndex) and proprietary (e.g. NVIDIA NeMo/NIM). • Competency writing ML code (for example, using PyTorch). • Experience with Python, Unix-like systems. • Ability to quickly prototype functionality into scripts for demos, integrations, troubleshooting, etc. • Understanding of hardware requirements associated with deep learning model training or inference, and how model attributes and performance factors affect it. • Knowledge of current AI landscape, including popular models, frameworks, applications, and capabilities. • Experience working with on-premise hardware / GPU clusters.

🏖️ Benefícios

• Health & Wellbeing • Personal & Professional Development • Unconditional Inclusion