Machine Learning Engineer Intern (E-Commerce Recommendation/Search Alliance) - 2026 Start (PhD)

ByteDance; Seattle (WA); On-site; USD 46,838 - 78,523; Full time

Benefits offered by this job

Health insurance

Life insurance

Wellbeing benefits

Paid holidays

Paid sick time

Housing allowance

Job summary

ByteDance is seeking a Machine Learning Engineer Intern (E-Commerce Recommendation/Search Alliance) for a 2026 start in Seattle. This role focuses on advancing our recommendation systems through ML, NLP, and CV techniques.

Candidates should be pursuing a PhD with strong data structures, algorithms, and ML knowledge. Final year or recent graduates in CS/Engineering are encouraged to apply. Interns receive comprehensive benefits and housing support where eligible.

Qualifications

• PhD student in CS/Engineering/OR or related field.
• Strong data structures, algorithms, and problem‑solving skills.
• Deep knowledge in ML, statistics, and big data engineering.

Responsibilities

• Design and implement ML algorithms to enhance recommendations.
• Apply ML, NLP, and CV techniques to analyze e-commerce data.
• Deploy scalable models for real-time query handling.
• Analyze datasets to derive strategic insights.
• Stay updated with ML developments and apply them.

Skills

Data structures

Algorithms

Problem solving

Machine learning

Statistics

Big data engineering

Distributed computing

Education

PhD in CS/Engineering/OR

Final year or recent graduate

Job description

Machine Learning Engineer Intern (E-Commerce Recommendation/Search Alliance) - 2026 Start (PhD)

Location: Seattle

Team: Technology

Employment Type: Intern

Job Code: A14677

Responsibilities

• Design and implement cutting‑edge machine learning algorithms to enhance our recommendation systems.
• Apply machine learning, natural language processing, and computer vision techniques to analyze e‑commerce data and interactions.
• Deploy and maintain scalable recommendation models for real‑time query handling and product suggestions.
• Analyze complex datasets to derive insights that guide strategic decisions.
• Stay up‑to‑date with the latest machine learning developments, incorporating them into your work.

Qualifications

Minimum Qualifications:

• Currently pursuing a PhD in Computer Science, Engineering, Operations Research, or related fields.
• Strong grasp of data structures, algorithms, and top‑notch problem‑solving skills.
• Profound knowledge in machine learning, statistics, and big data engineering.

Preferred Qualifications:

• Final year or recent graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Thorough understanding of data structures and algorithms, with excellent problem‑solving ability.
• Deep understanding of machine learning, statistics, scaling distributed computing, and big data engineering.

Job Information

The hourly rate range for this position in the selected city is $57‑$57.

Benefits

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.

EEO and Fair Chance

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:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
3. Exercising sound judgment.