Software Engineer - E-commerce Recommendation Infrastructure - San Jose

TikTok Inc.; San Jose (CA); On-site; USD 162,000 - 388,000; Full time

Job summary

TikTok Inc. is seeking engineers for the E-commerce Recommendation Infra team to build and optimize the infrastructure powering TikTok Shop recommendations.

The role focuses on scalable systems, online data pipelines, and collaborative problem solving with ML engineers. Responsibilities include delivering end-to-end infrastructure solutions, improving recommendation performance, and handling increasing user traffic and data volumes with robust systems.

Qualifications

• Bachelor's degree or above in CS or related fields; 3+ years of experience building scalable systems.
• Strong software development experience with C++, Java or other programming language.
• Good teamwork and communication skills; positive, optimistic, strong sense of ownership.

Responsibilities

• Build industry-leading globalized large-scale recommendation system.
• Design and build high performance online systems and reliable data pipelines.
• Optimize and evolve the system continuously to support the skyrocket increase in both user traffic and the data amount.
• Work with cross functional teams to deliver end-to-end infrastructure solutions to address critical product challenges and improve recommendation performance.

Skills

Software development

Teamwork

Ownership

Scalable systems

Education

Bachelor's degree in CS or related

Tools

C++

Java

Job description

Responsibilities

Our Team

E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-commerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the most stable and best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques.

• Build industry-leading globalized large-scale recommendation system;
• Design and build high performance online systems and reliable data pipelines;
• Optimize and evolve the system continuously so as to support the skyrocket increase in both user traffic as well as the data amount;
• Work with cross functional teams to deliver end-to-end infrastructure solutions to address critical product challenges and improve recommendation performance.

Qualifications

• Bachelor's degree or above, majoring in Computer Science or related fields, with 3+ years of experience building scalable systems;
• Strong software development experience with C++, Java or other programming language;
• Good teamwork and communication skills, positive and optimistic, and strong sense of ownership;
• Experienced in at least one of the following areas: personalized recommendations, search engine, advertising, machine learning infrastructure, distributed storage system, big data frameworks.

Job Information

Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $387600 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

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; and
3. Exercising sound judgment.

Responsibilities

Our Team

E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-commerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the most stable and best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques.

• Build industry-leading globalized large-scale recommendation system;
• Design and build high performance online systems and reliable data pipelines;
• Optimize and evolve the system continuously so as to support the skyrocket increase in both user traffic as well as the data amount;
• Work with cross functional teams to deliver end-to-end infrastructure solutions to address critical product challenges and improve recommendation performance.

Qualifications

• Bachelor's degree or above, majoring in Computer Science or related fields, with 3+ years of experience building scalable systems;
• Strong software development experience with C++, Java or other programming language;
• Good teamwork and communication skills, positive and optimistic, and strong sense of ownership;
• Experienced in at least one of the following areas: personalized recommendations, search engine, advertising, machine learning infrastructure, distributed storage system, big data frameworks.