Hybrid AI/ML Engineer — Graduate

Hewlett Packard Enterprise Company; San Jose (CA); Hybrid; USD 93,000 - 188,000; Full time

Benefits offered by this job

Hybrid work model

Career development programs

Job summary

Hewlett Packard Enterprise invites applications for the AI Workflow Specialist Graduate role, a hybrid position in California with two days per week in an HPE office. You will design and implement AI/ML models, prepare data pipelines, and collaborate with data scientists and engineers to translate requirements into scalable solutions.

Ideal candidates have 0–2 years of experience, strong Python/R/Java, ML libraries (TensorFlow, PyTorch, scikit-learn), and solid foundations in statistics.

Qualifications

• Bachelor’s degree in a quantitative field; Master’s desirable.
• 0–2 years of relevant experience or internship projects.
• Strong programming and ML fundamentals essential.

Responsibilities

• Designs, develops and implements AI/ML models and data pipelines.
• Gathers and analyzes data to train and test ML models and gain insights.
• Optimizes algorithms and hyperparameters for performance gains.
• Collaborates with data scientists, software engineers and product managers.
• Maintains documentation and presents results to stakeholders.
• Participates in design reviews and continuous improvement.

Skills

Python

R

Java

Statistics

Data analysis

Data visualization

SQL

ML concepts

Education

Bachelor's degree in CS/Engineering/Data Science

Master's degree desirable

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Hewlett Packard Enterprise invites applications for the AI Workflow Specialist Graduate role, a hybrid position in California with two days per week in an HPE office. You will design and implement AI/ML models, prepare data pipelines, and collaborate with data scientists and engineers to translate requirements into scalable solutions.

Ideal candidates have 0–2 years of experience, strong Python/R/Java, ML libraries (TensorFlow, PyTorch, scikit-learn), and solid foundations in statistics.