AI and Machine Learning Engineer
Mentions vibe coding and tools like GitHub CoPilot and Cursor — expects familiarity with AI-assisted, collaborative coding workflows.
About the Role
HPE is hiring an AI and Machine Learning Engineer to design, develop, and deploy ML models and algorithms for Hybrid Cloud products. The role focuses on data preparation, model training and evaluation, and collaborating with cross-functional teams to deliver scalable AI/ML solutions in a hybrid work model (≈2 days/week onsite).
Job Description
Role
HPE is seeking an AI/ML & Innovation Engineer to design, develop, and implement machine learning models and algorithms for Hybrid Cloud products. The role involves working with structured and unstructured data, applying statistical and deep learning techniques, and translating technical specifications into production code.
Key Responsibilities
- Design, develop, train, optimize, and scale ML and deep learning models to solve business problems.
- Prepare and preprocess large datasets (data cleaning, normalization, feature extraction, transformation).
- Select and tune algorithms and hyperparameters; perform cross-validation and evaluate models using metrics such as accuracy, precision, recall, and F1-score.
- Implement, test, debug, and document software and ML components; define and monitor performance metrics.
- Collaborate with data scientists, software engineers, and stakeholders to gather requirements, iterate on models, and present findings.
- Participate in design reviews and stand-up meetings; provide and receive feedback under guidance from engineering managers or team leads.
- Maintain or update business intelligence tools, dashboards, and relevant systems as required.
Requirements
- Bachelor’s degree in computer science, engineering, data science, machine learning, AI, or related quantitative discipline (Master’s desirable).
- Typically 2–4 years of relevant experience.
- Strong grounding in mathematics (linear algebra, calculus, probability) and statistics for model development and evaluation.
- Proficiency in programming (Python, R, or Java) and experience with ML libraries/frameworks (TensorFlow, PyTorch, scikit-learn, Keras).
- Experience with SQL for data manipulation and database querying.
- Familiarity with cloud infrastructure (e.g., AWS, Azure) and Linux/open source environments.
- Understanding of software engineering practices, version control (e.g., Git), DevOps/SRE principles, and production deployment of ML models.
- Practical experience with data preprocessing, feature engineering, model evaluation, hyperparameter tuning, and cross-validation.
- Strong communication skills for cross-functional collaboration and presenting technical concepts to non-technical stakeholders.
Tools & Technologies Mentioned
Python, R, Java, TensorFlow, PyTorch, scikit-learn, Keras, SQL, Git, GitHub CoPilot, Cursor, N8N, Windsurf, AWS, Azure, Linux.
Additional Skills
Design Thinking, Data Engineering, MLOps / Machine Learning Operations, scalability testing, security-first mindset, cross-domain knowledge, full-stack development fundamentals.
Work Model
Hybrid — expectation to work on average 2 days per week from an HPE office.
Benefits (summary)
Health & wellbeing programs, personal and professional development programs, inclusive workplace and flexible work arrangements.
Tech Stack
Skills
Experience Level
Employment Type
Benefits
- •Hybrid work (≈2 days/week onsite)
- •Health & Wellbeing programs
- •Personal & Professional Development programs
- •Inclusive workplace and flexible work arrangements