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Spring Intern, Scientist - Part Time

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Adswizz

2mo ago

  • Internship
    Full-time
    Off-cycle Internship
  • Data
    Research & Development
  • Oakland

AI generated summary

  • You should be a current MS/PhD student or recent grad in a quantitative field, with expertise in ML areas, strong communication skills, programming proficiency, and legal U.S. work rights.
  • You will research machine learning systems, design and analyze experiments, present findings, and perform additional duties as needed, collaborating closely with your mentor.

Requirements

  • Internship is open to current students enrolled in an MS/PhD degree (those graduating by January 2027 are preferred) and recent graduates who graduated within the 12-month period prior to the start of the internship.
  • Majors in computer science, machine learning, statistics or a related quantitative field preferred.
  • Expertise in one of the following areas: Deep Learning/GenAI, NLP/NLU, Computer Vision, Recommendation Systems, Music Information Retrieval, Statistics, and other related areas
  • Excellent communication skills with both technical and non-technical audiences.
  • Publications at machine learning conferences/journals.
  • Proficiency with Python, Java, or Scala.
  • Familiarity with common machine learning libraries (e.g., sk-learn, TensorFlow, PyTorch).
  • Experience with SQL (or proprietary equivalent).
  • Must have legal right to work in the U.S.

Responsibilities

  • Research and develop machine learning systems in your area of expertise in collaboration with your mentor
  • Design and analyze experiments to validate scientific hypotheses
  • Present your findings to appropriate audiences
  • Perform other duties as required.

FAQs

What is the location of this internship?

The internship is located in Oakland, California.

What type of internship is this position?

This is a part-time, fixed-term internship.

Who is eligible to apply for this internship?

Current students enrolled in an MS/PhD degree program (preferably graduating by January 2027) and recent graduates who graduated within the 12-month period prior to the start of the internship are eligible to apply.

What are the preferred majors for this internship?

Preferred majors include computer science, machine learning, statistics, or a related quantitative field.

What skills are required for this internship?

Proficiency in Python, Java, or Scala is required, along with familiarity with common machine learning libraries such as sk-learn, TensorFlow, or PyTorch, and experience with SQL.

What are the responsibilities of this internship?

Responsibilities include conducting research and developing machine learning systems, designing and analyzing experiments, presenting findings, and performing other duties as required.

What are the expected qualifications for applicants?

Applicants should have expertise in areas like Deep Learning/GenAI, NLP/NLU, Computer Vision, Recommendation Systems, or Music Information Retrieval, as well as excellent communication skills and a record of publications at machine learning conferences or journals.

Is there a specific compensation for this position?

The expected base salary for this position is $55 per hour, and it may vary based on skills, qualifications, and experience.

Does SiriusXM provide equal employment opportunities?

Yes, SiriusXM is an equal opportunity employer and does not discriminate based on any protected characteristics.

Can the requirements and duties of this internship change?

Yes, the requirements and duties described may be modified or waived by the company in its sole discretion without notice.

Technology for a Sound World.

Marketing & Advertising
Industry
201-500
Employees
2008
Founded Year

Mission & Purpose

AdsWizz (a SiriusXM company) is the audio-only adtech platform free from omnichannel imprecision and walled content gardens. Since 2008, we’ve set the bar for multi-format planning, buying and ad placement, designing advanced solutions to deepen the listening experience. We partner with enterprise publishers and advertisers to perfect the tools they need to execute campaigns with higher resonance through the power of sound. Depend on the one stack built for audio in every dimension.