Onsite AI and Machine Learning Engineer I Graduate role in San Jose, CA focused on building AI/ML products and data-driven solutions.

Collaborate with cross-functional teams to find data-driven improvement opportunities and convert business needs into technical implementations.
Ingest and integrate data from structured and unstructured enterprise sources, including Databricks and IT data platforms.
Design and build curated data models and analytical layers for reporting and downstream analytics.
Develop, optimize, and maintain data pipelines using SQL, Python, and orchestration tools.
Clean, transform, and prepare datasets to ensure dependable consumption across the organization.
Support data quality and observability across pipelines, workflows, and storage layers.
Integrate new data sources, APIs, and event streams into the data platform.
Create clear data documentation and explain technical concepts to non-technical stakeholders.
Stay current on modern data engineering tools, cloud technologies, and best practices.

Bachelor’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or a closely related quantitative discipline.
Master’s degree is desirable.
Typical experience: 0-2 years.
Programming proficiency in Python, R, or Java.
Strong familiarity with AI/ML libraries and frameworks such as TensorFlow, PyTorch, and scikit-learn.
Solid foundation in statistics, probability, linear algebra, calculus, and optimization for building and evaluating ML models.
In-depth knowledge of ML algorithms and concepts, including supervised and unsupervised learning, deep learning, neural networks, reinforcement learning, and natural language processing.
Experience with large datasets, including data preprocessing, data cleaning, and exploratory data analysis.
Experience with SQL and databases, plus data visualization tools such as Matplotlib or Tableau.

Health & Wellbeing: comprehensive suite of benefits supporting physical, financial, and emotional wellbeing.
Personal & Professional Development: programs aligned to career goals.
Unconditional Inclusion: flexibility to manage work and personal needs.

HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities.
If accommodation is needed during the application or interview process, request it by completing the secure form linked in the posting.
This option is reserved for applicants needing assistance or reasonable accommodation related to a disability.

HPE will never charge candidates a registration fee, hiring fee, or any other fee related to recruitment and hiring.
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AI and Machine Learning Engineer I Graduate

Job Description