AI/ML Solution Architect: Edge-to-Cloud Innovator

Hewlett Packard Enterprise; San Jose (CA); On-site; USD 160,000 - 325,000; Full time

Job summary

Hewlett Packard Enterprise is seeking a senior AI/ML engineering leader in California to drive research, design and deployment of scalable ML models for edge-to-cloud environments. You will guide model selection, data processing, and production readiness while collaborating with cross-functional teams and senior stakeholders.

The role demands deep ML expertise, strong communication, and a track record of deploying models at scale, with 7–10 years of experience and a relevant advanced degree.

Qualifications

• Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.
• Typically, 7-10 years’ experience.
• Proficiency in Python, R, or Java and production-level coding practices.

Responsibilities

• Conduct research and stay up to date with AI/ML advancements and frameworks.
• Collaborate with cross-functional teams to design scalable AI/ML solutions.
• Develop, train, and optimize machine learning models on large datasets.
• Deploy models to production with attention to scalability, performance and security.
• Lead design reviews and mentor junior team members.
• Present insights and recommendations to senior stakeholders.

Skills

Python

R

Java

TensorFlow

PyTorch

scikit-learn

Keras

NLP

ML algorithms

Data mining

Statistical modeling

Communication skills

Education

Bachelor's or master's degree in computer science, engineering, data science, ML, AI, or related field

Tools

Git

Job description

Hewlett Packard Enterprise is seeking a senior AI/ML engineering leader in California to drive research, design and deployment of scalable ML models for edge-to-cloud environments. You will guide model selection, data processing, and production readiness while collaborating with cross-functional teams and senior stakeholders.

The role demands deep ML expertise, strong communication, and a track record of deploying models at scale, with 7–10 years of experience and a relevant advanced degree.