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Machine Learning Engineer Intern; Commerce Ads - Summer; BS​/MS

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Ellis Technologies, Inc.
Full Time, Seasonal/Temporary, Apprenticeship/Internship position
Listed on 2026-06-06
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: Machine Learning Engineer Intern (Commerce Ads) - 2026 Summer (BS/MS)

Location:

San Jose

Employment Type:

Intern

Job Code: A12428A

Summer Start Dates:
May 11th, 2026 May 18th, 2026 May 26th, 2026 June 8th, 2026 June 22nd, 2026

Responsibilities
  • Build highly scalable machine learning systems and state-of-the-art machine learning models to improve ads ranking quality and optimize advertisers' marketing strategies. Examples include but are not limited to click through rate prediction, conversion rate prediction, intelligent format selection and user journey optimization.
  • Explore, develop and experiment with new features to improve model accuracy.
  • Understand ads platform objectives and take full advantage of modern machine learning to improve ads relevance, quality, and quantity delivered to end-users.
  • Collaborate with Product Managers, Designers, and other disciplines to explore the next generation of shopping experiences on Tik Tok.
Qualifications
  • Currently pursuing an Undergraduate/Master in Computer Science, Computer Engineering or a related technical discipline.
  • Solid programming skills, including but not limited to:
    Go, C/C++, Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
  • Good analytical thinking capability. Have essential knowledge and skills in statistics.
  • Good theoretical grounding in the machine and deep learning concepts and techniques (CNN/RNN/LSTM, etc.).
  • Familiar with the architecture and implementation of at least one mainstream machine learning programming framework (Tensor Flow/PyTorch/MXNet), familiar with its architecture and implementation mechanism.
  • Must be able to commit to a 12-week full-time work period during Summer 2026.

Preferred Qualifications:

  • Good understanding in one of the following domains: ads bidding & auction, ads quality control, and online advertising systems (familiar with one or more of these terms: CPC/CPM, CTR/CVR, Ranking /Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB).
  • Experience in resource management and task scheduling with large-scale distributed software (such as Spark and Tensor Flow).
  • Relevant work or research experiences in search and recommendation.
Job Information

The hourly rate range for this position in the selected city is $45- $60.

Benefits

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.

Equal

Opportunity Statement

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

  • Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
  • Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
  • Exercising sound judgment.
  • By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here:

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