AI Solution Engineer
Job Description:
• Architect, build, and deliver AI solutions in demos and proof-of-concepts.
• Lead technical discussions to propose integrated solutions.
• Demo AI solutions to address customer use cases.
• Lead Proof-of-Concepts / Proof-of-Value engagements.
• Assist in product or technical issues for initial sales or renewals.
• Help enable prospects and partners on HPE's value in AI landscape.
Requirements:
• 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.
• Understanding of hardware requirements associated with deep learning model training or inference.
• 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.
Benefits:
• Health & Wellbeing
• Personal & Professional Development
• Unconditional Inclusion
Apply Now
Apply Now
• Architect, build, and deliver AI solutions in demos and proof-of-concepts.
• Lead technical discussions to propose integrated solutions.
• Demo AI solutions to address customer use cases.
• Lead Proof-of-Concepts / Proof-of-Value engagements.
• Assist in product or technical issues for initial sales or renewals.
• Help enable prospects and partners on HPE's value in AI landscape.
Requirements:
• 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.
• Understanding of hardware requirements associated with deep learning model training or inference.
• 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.
Benefits:
• Health & Wellbeing
• Personal & Professional Development
• Unconditional Inclusion
Apply Now
Apply Now