Hewlett Packard Enterprise · 5 hours ago

AI Solution Engineer (Determined AI)

Texas, United States

Full-time

Remote

Mid Level

$130K/yr - $300K/yr

4+ years exp

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Responsibilities

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 (either existing or built by you) to prospects that address their use cases or desired AI outcomes.

Lead Proof-of-Concepts / Proof-of-Value engagements for HPE prospects that demonstrate clear value from HPE's AI offerings, likely in combination with 3rd Party and Open Source components.

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 and how HPE and partner solutions can help solve real world business problems.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Machine LearningDeep LearningKubernetesLLM frameworksML code (PyTorch)PythonPrototyping scriptsDeep learning hardwareAI landscape knowledgeOn-premise hardwareLangChainLllamaIndexNVIDIA NeMo/NIMUnix-like systemsGPU clustersTechnologist evangelism

Required

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.

Strong communicator, presenter and technologist evangelist.

Curiosity/interest in continuous learning to stay at the forefront of challenges which can be addressed through AI.