(General Hire) Machine Learning Engineer (all levels) , TikTok Recommendation
Jul 14, 2026 San Jose
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 5,001 - 10,000 employees
- Industry: Entertainment & Gaming
Responsibilities
About the Team
Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is a diverse group of world-level researchers and engineers, who develop and support the production recommendation systems that drive product impact. The team is fast-paced, collaborative and impact-driven.
What is General Hire ?
If you're applying under the General Hire track for the TikTok Recommendation Organization, you'll go through a unified interview process designed to assess your fit across the whole TikTok Recommendation Organization. Based on your background, experience, interests, and interview performance, we'll help identify one or more teams that are the best match for you.
Responsibilities - What You'II Do
- Develop recommendation systems that improve user experience and platform content ecosystem.
- Build machine learning systems and pipelines to address critical product challenges.
- Own a full stack machine learning system(s), lead its development, support, and improvements.
- Collaborate with cross functional teams to design product strategies and build solutions to grow TikTok in the US market.
Qualifications
Minimum Qualifications
- B.S. in Computer Science, Machine Learning, Statistics, or equivalent experience.
- Strong coding skills in Python and/or C++, with solid foundations in data structures and algorithms.
- Experience building machine learning systems using frameworks such as PyTorch or TensorFlow.
- Proven expertise in recommendation systems, ranking, retrieval, personalization, applied machine learning, or large-scale ML infrastructure.
- Strong communication and collaboration skills.
Preferred Qualifications
- Ph.D. in Recommendation Systems, Machine Learning, or equivalent experience.
- Strong background in user modeling, recommendation, ranking, retrieval, or large-scale ML systems.
- Experience with LLM-powered recommendation, multimodal recommendation, or reinforcement learning.
- Publications in ML, AI, or RecSys conferences are a strong plus.
Job Information
[For Pay Transparency] Compensation Description (annually)
The base salary range for this position in the selected city is $254400 - $588000 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:
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; and
3. Exercising sound judgment.
About the Team
Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is a diverse group of world-level researchers and engineers, who develop and support the production recommendation systems that drive product impact. The team is fast-paced, collaborative and impact-driven.
What is General Hire ?
If you're applying under the General Hire track for the TikTok Recommendation Organization, you'll go through a unified interview process designed to assess your fit across the whole TikTok Recommendation Organization. Based on your background, experience, interests, and interview performance, we'll help identify one or more teams that are the best match for you.
Responsibilities - What You'II Do
- Develop recommendation systems that improve user experience and platform content ecosystem.
- Build machine learning systems and pipelines to address critical product challenges.
- Own a full stack machine learning system(s), lead its development, support, and improvements.
- Collaborate with cross functional teams to design product strategies and build solutions to grow TikTok in the US market.
Minimum Qualifications
- B.S. in Computer Science, Machine Learning, Statistics, or equivalent experience.
- Strong coding skills in Python and/or C++, with solid foundations in data structures and algorithms.
- Experience building machine learning systems using frameworks such as PyTorch or TensorFlow.
- Proven expertise in recommendation systems, ranking, retrieval, personalization, applied machine learning, or large-scale ML infrastructure.
- Strong communication and collaboration skills.
Preferred Qualifications
- Ph.D. in Recommendation Systems, Machine Learning, or equivalent experience.
- Strong background in user modeling, recommendation, ranking, retrieval, or large-scale ML systems.
- Experience with LLM-powered recommendation, multimodal recommendation, or reinforcement learning.
- Publications in ML, AI, or RecSys conferences are a strong plus.
About the Team
Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is a diverse group of world-level researchers and engineers, who develop and support the production recommendation systems that drive product impact. The team is fast-paced, collaborative and impact-driven.
What is General Hire ?
If you're applying under the General Hire track for the TikTok Recommendation Organization, you'll go through a unified interview process designed to assess your fit across the whole TikTok Recommendation Organization. Based on your background, experience, interests, and interview performance, we'll help identify one or more teams that are the best match for you.
Responsibilities - What You'II Do
- Develop recommendation systems that improve user experience and platform content ecosystem.
- Build machine learning systems and pipelines to address critical product challenges.
- Own a full stack machine learning system(s), lead its development, support, and improvements.
- Collaborate with cross functional teams to design product strategies and build solutions to grow TikTok in the US market.
Qualifications
Minimum Qualifications
- B.S. in Computer Science, Machine Learning, Statistics, or equivalent experience.
- Strong coding skills in Python and/or C++, with solid foundations in data structures and algorithms.
- Experience building machine learning systems using frameworks such as PyTorch or TensorFlow.
- Proven expertise in recommendation systems, ranking, retrieval, personalization, applied machine learning, or large-scale ML infrastructure.
- Strong communication and collaboration skills.
Preferred Qualifications
- Ph.D. in Recommendation Systems, Machine Learning, or equivalent experience.
- Strong background in user modeling, recommendation, ranking, retrieval, or large-scale ML systems.
- Experience with LLM-powered recommendation, multimodal recommendation, or reinforcement learning.
- Publications in ML, AI, or RecSys conferences are a strong plus.
Job Information
[For Pay Transparency] Compensation Description (annually)
The base salary range for this position in the selected city is $254400 - $588000 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:
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; and
3. Exercising sound judgment.
Responsibilities
ResponsibilitiesAbout the Team
Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is a diverse group of world-level researchers and engineers, who develop and support the production recommendation systems that drive product impact. The team is fast-paced, collaborative and impact-driven.
What is General Hire ?
If you're applying under the General Hire track for the TikTok Recommendation Organization, you'll go through a unified interview process designed to assess your fit across the whole TikTok Recommendation Organization. Based on your background, experience, interests, and interview performance, we'll help identify one or more teams that are the best match for you.
Responsibilities - What You'II Do
- Develop recommendation systems that improve user experience and platform content ecosystem.
- Build machine learning systems and pipelines to address critical product challenges.
- Own a full stack machine learning system(s), lead its development, support, and improvements.
- Collaborate with cross functional teams to design product strategies and build solutions to grow TikTok in the US market.
Qualifications
QualificationsMinimum Qualifications
- B.S. in Computer Science, Machine Learning, Statistics, or equivalent experience.
- Strong coding skills in Python and/or C++, with solid foundations in data structures and algorithms.
- Experience building machine learning systems using frameworks such as PyTorch or TensorFlow.
- Proven expertise in recommendation systems, ranking, retrieval, personalization, applied machine learning, or large-scale ML infrastructure.
- Strong communication and collaboration skills.
Preferred Qualifications
- Ph.D. in Recommendation Systems, Machine Learning, or equivalent experience.
- Strong background in user modeling, recommendation, ranking, retrieval, or large-scale ML systems.
- Experience with LLM-powered recommendation, multimodal recommendation, or reinforcement learning.
- Publications in ML, AI, or RecSys conferences are a strong plus.
Additional Information
- Salary: $254,400 – $588,000
- Posted: Jul 14, 2026