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Personal Systems Machine Learning Internship

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  • Internship
    Full-time
    Off-cycle Internship
  • Data
  • Austin

Requirements

  • Education & Experience Required:
  • Master or PhD Candidate in Computer Science or related technical areas
  • Preferred Majors:
  • Computer Science, Computer Engineering, Artificial Intelligence and Machine Learning, Data Science
  • Preferred Knowledge & Skills:
  • Experience in C, C++ programming and Python
  • Experience with one or more deep learning frameworks (Caffe, Caffe2, PyTorch, Tensorflow)
  • Experience with OpenCV
  • Good technical judgment and initiative
  • Demonstrated ability to work effectively as a member of a team
  • Strong oral and written communications skills

Responsibilities

  • Participate in cutting-edge research in deep learning for computer vision applications.
  • Design and implement computer vision and deep learning algorithms for analyzing images and videos in real time
  • Prepare training, validation, and testing dataset, label ground truth, and analyzing result
  • Document experimental results, and file patent disclosures
  • Collaborate with project team members, as well as engineers across company to meet research goals

FAQs

What is the duration of the Personal Systems Machine Learning Internship?

The internship is designed to last for 12 weeks during the Summer 2024.

Is this internship paid?

Yes, it is a paid internship.

What kind of projects will interns be involved in?

Interns will work on significant, impactful projects related to computer vision and deep learning; the program emphasizes hands-on experience rather than administrative tasks like paper filing.

What qualifications are required for this internship?

The internship is open to Master’s and PhD candidates who have a passion for deep learning and its application in industrial settings.

Will there be opportunities for networking and professional development during the internship?

Yes, the internship program includes networking opportunities, executive speakers, community involvement, and other professional development activities.

What area of research does the Personal Systems Machine Learning Internship focus on?

The internship focuses on research and development in the area of computer vision and deep learning.

What type of candidates is HP looking for in this internship?

HP is looking for candidates who are innovative, possess a diverse set of skills and experiences, and are enthusiastic about solving challenging deep learning problems.

Will interns have the chance to impact real-world products?

Yes, interns will contribute to successful products used by millions of people.

What kind of experiences can interns expect at HP?

Interns can expect a thoughtful balance of work experience, networking, community involvement, and fun during their internship.

Are there any specific technologies or tools that interns will be working with?

While the job description does not specify, interns will likely work with various deep learning frameworks and tools relevant to computer vision and machine learning applications.

Information Technology & Services

Technology
Industry
10,001+
Employees
1939
Founded Year

Mission & Purpose

HPE (Hewlett Packard Enterprise) is a global technology company that provides a comprehensive range of IT solutions and services. They offer hardware, software, and hybrid IT infrastructure solutions, including servers, storage systems, networking equipment, and cloud computing services. HPE's ultimate mission is to help their clients thrive in the digital age by providing transformative technology solutions that drive innovation, enhance productivity, and enable business growth. Their purpose is to empower organisations to harness the power of technology and data to solve complex challenges, optimise their IT infrastructure, and accelerate their digital transformation. HPE strives to be a trusted partner, delivering cutting-edge technology and expertise that enables their clients to adapt, innovate, and stay ahead in an ever-changing and competitive marketplace.