Hewlett-Packard/HP

Personal Systems Machine Learning Internship

Hewlett-Packard/HP

Austin, TX, USA
Full-TimeDepends on ExperienceSenior LevelMasters
Job Description

At Hewlett-Packard/HP, we are looking for a motivated and creative Personal Systems Machine Learning Intern to join our team. This is a unique opportunity for a self-starter who is passionate about technology and machine learning to gain valuable experience and be part of a dynamic and innovative team. The successful applicant will need to have a strong academic background in computer science or a related field, as well as practical experience in machine learning and related technologies. They will need to be able to think outside the box and be comfortable working with a diverse range of people. Additionally, they will need to have excellent communication skills and be able to work independently as well as with a team. The successful candidate will have the opportunity to work on innovative projects that will help shape the future of the personal systems industry. They will be part of a team of experts, with the potential to grow and develop their skills and knowledge. This is an exciting opportunity for someone who is looking to make a difference and to be part of a team that is creating the future.

Responsibilities:

  1. Develop machine learning models and algorithms for personal systems applications.
  2. Utilize programming languages such as Python, R, and MATLAB to create and maintain machine learning models.
  3. Work with a team to develop and implement machine learning initiatives.
  4. Assist with data collection, analysis, and interpretation.
  5. Research new technologies and methods for machine learning applications.
  6. Participate in design and code reviews.
  7. Prepare technical reports, presentations, and other documentation as required.
  8. Collaborate with other departments to identify and discuss potential applications of machine learning.
  9. Utilize problem-solving skills to troubleshoot and resolve technical issues. 10.Keep up to date with the latest trends and advancements in the field of machine learning.
Where is this job?
This job is located at Austin, TX, USA
Job Qualifications
  • Java

  • Bachelor's Degree In Computer Science

  • Mathematics

  • Statistics

  • Or A Related Field

  • Machine Learning

  • Proficiency In Programming Languages Such As Python

  • And C++

  • Strong Understanding Of Machine Learning Algorithms And Principles

  • Knowledge Of Deep Learning Frameworks Such As Tensorflow And Keras

  • Experience With Data Science Tools Such As Scikit-Learn

  • Knowledge Of Software Engineering Processes And Principles

Required Skills
  • Sql

  • Python

  • Machine Learning

  • Deep Learning

  • Scikit-learn

  • Tensorflow

  • Data Visualization

  • Algorithm design

  • Data Mining

  • Keras

  • Data science

  • NLP

  • Statistics

  • AI

  • Model Optimization

Soft Skills
  • Communication

  • Interpersonal

  • Leadership

  • Negotiation

  • Time management

  • Critical thinking

  • Teamwork

  • Adaptability

  • Problem-Solving

  • Organizational

Compensation

According to JobzMall, the average salary range for a Personal Systems Machine Learning Internship in Austin, TX, USA is $36,000 - $51,000 per year. The salary range will depend on a variety of factors, including experience, qualifications, and the size of the company.

Additional Information
Hewlett-Packard/HP is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
Required LanguagesEnglish
Job PostedOctober 23rd, 2023
Apply BeforeMay 22nd, 2025
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About Hewlett-Packard/HP

The Hewlett-Packard Company or Hewlett-Packard is an American multinational information technology company headquartered in Palo Alto, California.

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