AI and Machine Learning Engineer I Graduate

Develops and programs integrated software algorithms to structure, analyze and leverage structured and unstructured data in product and systems applications. Can work with large scale computing frameworks, data analysis systems, and modeling environments.

Uses machine learning and statistical modeling techniques to improve product/system performance, data management, quality, and accuracy. Formulates descriptive, diagnostic, predictive and prescriptive insights/algorithms and translates technical specifications into code. Applies, optimizes and scales deep learning technologies and algorithms to give computers the capability to visualize, learn and respond to complex situations. Documents procedures for installation and maintenance, completes programming, performs testing and debugging, defines and monitors performance metrics.

Contributes to the success of HPE by translating customer requirements and industry trends into AI/ML products, solutions, and systems improvement projects.

Management Level Definition:

Contributes to assignments of limited scope by applying technical concepts and theoretical knowledge acquired through specialized training, education, or previous experience. Acts as team member by providing information, analysis and recommendations in support of team efforts. Exercises independent judgment within defined parameters., * Partner with cross-functional teams to identify opportunities for data-driven improvements and translate business needs into technical solutions.

• Ingest and integrate data from structured and unstructured enterprise systems, including Databricks and IT data platforms.
• Design and build curated data models and analytical layers to support reporting and downstream analytics.
• Develop, optimize, and maintain pipelines using SQL, Python, and orchestration tools.
• Clean, transform, and prepare datasets for reliable consumption across the business.
• Ensure data quality and observability across pipelines, workflows, and storage layers.
• Integrate new data sources, APIs, and event streams into the platform.
• Create clear data documentation and communicate technical concepts to non-technical stakeholders.
• Stay current with modern data engineering tools, cloud technologies, and best practices.

• Bachelor’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline. Master’s degree is desirable.
• Typically, 0-2 years’ experience.

Knowledge and Skills:

• Proficiency in programming languages such as Python, R, or Java is required. Knowledge of libraries and frameworks commonly used in AI and machine learning, such as TensorFlow, PyTorch, or scikit-learn, is highly beneficial.
• A solid understanding of statistics, probability, linear algebra, calculus, and optimization methods is crucial for building and evaluating machine learning models.
• In-depth knowledge of machine learning algorithms, techniques, and concepts is essential. This includes supervised and unsupervised learning, deep learning, neural networks, reinforcement learning, and natural language processing.
• Proficiency in working with large datasets, data pre-processing, data cleaning, and exploratory data analysis is necessary. Experience with SQL and databases and data visualization tools like Matplotlib or Tableau is required.

“The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.

• United States of America: Annual Salary USD 92,700 - 187,800 in California The listed salary range reflects base salary. Variable incentives may also be offered.”

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.